Citation
Low-Power Radar System for Remote Detection of Heartbeat and Respiration Using Double-Sideband Transmission and Frequency-Tuning Technique

Material Information

Title:
Low-Power Radar System for Remote Detection of Heartbeat and Respiration Using Double-Sideband Transmission and Frequency-Tuning Technique
Creator:
XIAO, YANMING ( Author, Primary )
Copyright Date:
2008

Subjects

Subjects / Keywords:
Antennas ( jstor )
Block diagrams ( jstor )
Oscillators ( jstor )
Radar ( jstor )
Receivers ( jstor )
Respiration ( jstor )
Sidebands ( jstor )
Signal detection ( jstor )
Signals ( jstor )
Vital signs ( jstor )

Record Information

Source Institution:
University of Florida
Holding Location:
University of Florida
Rights Management:
Copyright Yanming Xiao. Permission granted to the University of Florida to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Embargo Date:
5/31/2010
Resource Identifier:
659898721 ( OCLC )

Downloads

This item is only available as the following downloads:


Full Text

PAGE 1

LOW-POWER RADAR SYSTEM FOR REMOTE DETECTION OF HEARTBEAT AND RESPIRAITON USING DOUBLESIDEBAND TRANSMISSION AND FREQUENCY-TUNING TECHNIQUE By YANMING XIAO A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2007

PAGE 2

Copyright 2007 by Yanming Xiao

PAGE 3

ACKNOWLEDGMENTS I would like to express my sincere gratitude to my supervisory committee chair, Dr. Jenshan Lin, who provided the free, creativ e and friendly atmosphere needed for an invaluable research expe rience. Without his knowledge , experience, vision, and encouraging attitude, this work would be impo ssible. I also sincerely appreciate the time and effort given by the members of my supe rvisory committee (Dr. Rizwan Bashirullah, Dr. William Eisenstadt , and Dr. Yiider Tseng) . I thank them for their interests in my work and serving on my supervisory committee. I am also extremely grateful to Changzhi Li, my coworker, who contributes his full efforts and time to the development and improvement of the system. Without his generous and competent help, I could not ha ve been completed my PhD work in the given time. I am also thankful to my colleagues (Tien-Yu Chang, Lance Covert, Jerry Jun, JaeShin Kim, SangWon Ko, Ching-Ku Liao, Ashok Verma, Xiuge Yang, and Hyeopgoo Yeo) in the Radio Frequency System On Chip (RFSOC) Group, for all the help they offered. My thanks also go to my other colleagues (Changhua Cao, Yanping Ding, Yu Su) in the Department of Electrical and Computer Engineering, especially everyone in the electronics area, for their indispensa ble role in my study and research. I dedicate this work and my deepest love to my parents and sisters who have given me the utmost trust and support to explore my life. iii

PAGE 4

TABLE OF CONTENTS page ACKNOWLEDGMENTS .................................................................................................iii LIST OF TABLES ............................................................................................................vii LIST OF FIGURES .........................................................................................................viii ABSTRACT ......................................................................................................................xii CHAPTER 1 INTRODUCTION........................................................................................................1 1.1 Working Methodology ............................................................................................1 1.2 Chest-Wall Motion due to Heartbeat and Respiration............................................4 1.3 History ....................................................................................................................5 1.4 Proposed System With Double-Sideband Transmission ........................................9 1.5 Organization .........................................................................................................10 2 LIMITATIONS AND DOUBLE-SIDEBAND TRANSMISSION............................12 2.1 Phase Noise and Clutter Noise .............................................................................13 2.2 DC Offset ..............................................................................................................15 2.3 Null Point and Optimum Point .............................................................................16 2.3.1 Single-Tone Transmission ..........................................................................16 2.3.2 Double Sideband Transmission ..................................................................20 2.3.2.1 Double sideband ...............................................................................22 2.3.2.2 Frequency tuning technique .............................................................30 2.4 Harmonic Distortion .............................................................................................32 2.5 Summary ...............................................................................................................33 3 SYSTEM ARCHITECTURES...................................................................................34 3.1 Radar Range Equation ..........................................................................................34 3.1.1 Antenna Gain G ..........................................................................................35 3.1.2 Radar Cross Section ................................................................................36 3.1.3 Channel Noise ............................................................................................37 3.2 RF Section ............................................................................................................37 3.2.1 RF Receiver ................................................................................................38 iv

PAGE 5

3.2.1.1 Receiver bandwidth ..........................................................................38 3.2.1.2 Receiver noise figure ........................................................................38 3.2.1.3 Receiver sensitivity ..........................................................................39 3.2.2 Transmitter Power ......................................................................................39 3.2 Baseband Section ..................................................................................................40 3.3 Signal Processing Section .....................................................................................42 3.4 Summary ...............................................................................................................45 4 KA-BAND VITAL SIGN MONITORING SYSTEM...............................................47 4.1 System Description ...............................................................................................47 4.1.1 RF Section..................................................................................................48 4.1.2 Antennas .....................................................................................................50 4.1.3 Baseband Circuitry .....................................................................................52 4.1.4 Signal Processing ........................................................................................53 4.2 Ka-band Link Budget ...........................................................................................53 4.3 Measurement Results ............................................................................................56 4.3.1 Heartbeat and Respiration Measured at Short Distance .............................56 4.3.2 Heartbeat and Respiration Measured over Variable Distance ....................58 4.3.3 Heartbeat and Respiration Measurement with Obstacles ...........................59 4.3.4 Single-Tone Sound Measurement ..............................................................60 4.3.5 Null Point Elimination with Frequency Sweeping .....................................62 4.3.6 Measurement under the Different Power Levels and from Different Body Sides.......................................................................................................63 4.4 Harmonic Interference at Ka-band .......................................................................65 4.5 Summary ...............................................................................................................67 5 5 GHZ PORTABLE VITAL SIGN MONITORING MODULES.............................69 5.1 Portable Indirect-Conversion Module ..................................................................70 5.1.1 RF Transceiver Section ..............................................................................70 5.1.2 Antennas .....................................................................................................74 5.1.3 Baseband Section ........................................................................................75 5.1.4 Signal Processing Section ...........................................................................75 5.1.5 Link Budget................................................................................................75 5.1.6 Measurement Results ..................................................................................76 5.2 Direct-Conversion Non-quadrature Module .........................................................79 5.2.1 Link Budget................................................................................................81 5.2.2 Measurement Results ..................................................................................81 5.3 Direct-Conversion Quadrature Module ................................................................83 5.4 Comparison ...........................................................................................................85 5.4.1 Direct-Conversion Non-quadrature Module ...............................................86 5.4.2 Direct-Conversion Quadrature Sensor Module ..........................................86 5.4.3 Double-Sideband Indirect-C onversion Sensor Module ..............................87 5.4.4 Comparisons ...............................................................................................88 5.5 Summary ...............................................................................................................89 v

PAGE 6

6 5 GHZ VITAL SIGN SENSOR CHIP DESIGN........................................................91 6.1 RF Blocks .............................................................................................................92 6.1.1 Low Noise Amplifier ..................................................................................92 6.1.2 Active Mixers .............................................................................................93 6.1.3 IF Amplifier ................................................................................................95 6.1.4 Passive Mixer .............................................................................................95 6.1.5 Oscillators ...................................................................................................97 6.1.6 Overall Circuit ............................................................................................98 6.2 Summary .............................................................................................................101 7 SUMMARY AND FUTURE WORK......................................................................102 7.1 Summary .............................................................................................................102 7.2 Future Work ........................................................................................................104 7.2.1 5 GHz Chip Testing ..................................................................................104 7.2.2 Multi-Target Monitoring System .............................................................105 7.2.3 Tunable Wideband or Multi-Band System ...............................................106 APPENDIX: RANGE CORRELATION EFFECTS......................................................108 REFERENCES ................................................................................................................114 BIOGRAPHICAL SKETCH ...........................................................................................117 vi

PAGE 7

LIST OF TABLES Table page 3-1 RCS of some typical targets. ....................................................................................37 4-1 Ka-band system RF section buildi ng blocks and their specifications. .....................49 4-2 Received signal power for 27 GHz system ..............................................................53 4-3 Receiver sensitivity and link margin ........................................................................55 4-4 Heart-Rate Accuracy Comparison Be tween a Single Patch Antenna and a 4x4 Antenna Array over Different Distances from 0.5 Meters to 2.5 Meters. ................59 4-5 Summary of Heart-Ra te Detection Accuracy ...........................................................64 5-1 Components used in 5 GHz m odule and their specifications. ..................................71 5-2 Received signal power for 5 GHz monitoring system .............................................75 5-3 Receiver sensitivity and link margin ........................................................................76 5-4 Heart-rate accuracy vs. the detecting distance .........................................................77 5-5 Components used in 5 GHz dire ct-conversion nonquadrature module. .................80 5-6 Received signal power for 5 GHz monitoring system .............................................81 5-7 Detection accuracy versus detecting distance ..........................................................85 5-8 Detection accuracy summary of three modules*......................................................89 vii

PAGE 8

LIST OF FIGURES Figure page 1-1 Signal flow of vital sign monitoring system. .............................................................2 1-2 Block diagram of a1150-MHz microwave life-detection system. .............................7 1-3 Block diagram of a 2.4-GHz chip-lev el vital-sign monitoring system. .....................8 1-4 Block diagram of a UWB radar vital sign monitoring system. ..................................9 2-1 Four limitations in vital sign monitoring system design. .........................................12 2-2 Transmitted and received signal spectra. .................................................................14 2-3 Relationship of DC offset and wanted signals. ........................................................15 2-4 Optimum points and null points distri bute along the path away from the radar. .....18 2-5 Block diagram of a quadrature demodulation. .........................................................19 2-6 General block diagram of an indirect-conversion architecture. ...............................21 2-7 Optimum points and null points distri bute along the path away from the radar for double sideband transmission. ............................................................................22 2-8 Case of L and U separated by an odd multiple of . B ( t ) (red line) is the addition of BL( t ) (black line) and BU( t ) (blue line). ..................................................24 B B 2-9 Case of L and U separated by an odd multiple of /2. B ( t ) is the addition of BL( t ) (null point) and BU( t ) (optimum point).....................................................................26 B B 2-10 Case of L and U separated by by an arbitrary angle other than k and k + /2. B ( t ) is the addition of BL( t ) and BU( t ). ......................................................................28 B B 2-11 Global Optimum points and null po ints distribute for double sideband transmission along the path away from the radar. ....................................................29 2-12 Global null points and optimum points distribute versus both distance and frequency. d and f are two variables. ........................................................................30 viii

PAGE 9

2-13 The distribution of null points (global and local) with different LO1 frequency f1...............................................................................................................................32 3-1 Block diagram of the vital sign monitoring system. ................................................34 3-2 IEEE RF safety guideline. ........................................................................................40 3-3 Baseband section includes PreAMP, BPF, and BB_AMP. ......................................40 3-4 Schematic of the PreAMP and BB_AMP. ...............................................................41 3-5 Schematic of the band pass filter.. ............................................................................42 3-6 Transfer function of BPF with bandwidth of 0.2 Hz..........................................42 3-7 LabVIEW block diagram for real time signal analysis. ...........................................43 3-8 A screen capture of th e real time signal analysis. ....................................................46 4-1 Block diagram of the Ka-band vital sign monitoring system. ..................................48 4-2 The output spectrum of the transmitter, measured at the antenna connector. ..........49 4-3 Photography of two types of antennas.....................................................................51 4-4 Radiation gain and S11 of two types of antennas. .....................................................52 4-5 Propagation channel of the Ka-band monitoring system. ........................................53 4-6 Block diagram of the RF section of the Ka-band monitoring system. .....................54 4-7 Schematic of the Ka-band monitoring system. ........................................................55 4-8 ADS simulation results on heartbeat detection. .......................................................56 4-9 Measurement setup for heartb eat and respiration detection.....................................57 4-10 Detected (solid line) and reference (das hed line, not in the same scale) signals. ....58 4-11 Baseband signal B ( t ) is shown at the top, follo wed by the signal processed respiration and heartbeat signals. .............................................................................59 4-12 Measurement setup having a 4’x4’ 2-cm-thick wood board inserting between the monitoring system and the subject. ..........................................................................60 4-13 Result of Doppler radar sensor used for sound detection. ........................................61 4-14 Heartbeat detection at null point and optimum point. ..............................................62 ix

PAGE 10

4-15 Topview of the test setup.........................................................................................63 4-16 Detected signal at 2-m distance ................................................................................65 4-17 Normalized spectrum comparison at 1.5-m distance. ..............................................66 4-18 Simulated normalized spectrum comparison ...........................................................67 5-1 Block diagram of a 5-GHz vital sign monitoring system. ........................................70 5-2 Schematic of a 5 GHz oscillator. ..............................................................................72 5-3 Output power spectrum for a discrete designed oscillator. ......................................72 5-4 Photography of the indirect-conversion circuit board. .............................................73 55 Power spectrum of the transmitter output. ...............................................................73 5-6 Photography and Measured S11 of printed 2x2 patch antenna array. .......................74 5-7 Photograph of the system setup. ...............................................................................76 5-8 Detected signals for 5-GHz non-contact vital sign monitoring system. ..................78 5-9 Normalized spectrums of the baseband signal .........................................................79 5-10 Block diagram of a 5-GHz indi rect-conversion non-quadrature module. ................80 5-11 Photography of the direct-conversion non-quadrature circuit board. .......................81 5-12 Detected time domain signal and hear t rate from the front side of the body. ..........82 5-13 Detected time domain signal and hear t rate from the back side of the body. ..........82 5-14 Block diagram of a 5-GHz direct-conversion quadrature module. ..........................83 5-15 Photography of the direct-c onversion quadrature circuit board. ..............................84 5-16 Detected signals for I and Q channel. ......................................................................85 5-17 An example of detected signal and norm alized spectrum of the direct-conversion quadrature detector. ..................................................................................................87 6-1 Block diagram of 5 GHz on-chip monitoring system. .............................................91 6-2 Schematic of a 5-GHz LNA and its simulated performance. ...................................93 6-3 Schematic of an active double-balan ced mixer and its simulated performance. ......95 6-4 Schematic of an IF amplifie r and its simulated performance. ..................................96 x

PAGE 11

6-5 Schematic of a passive mixer and its simulated performance. .................................96 6-6 Simplified schematic of a 5 GHz VCO. ...................................................................98 6-7 Schematic of a 200MHz ring oscillator. ...................................................................99 6-8 Simulated output spectrum. The uppe r two are transmitter outputs in time domain and frequency domain. ..............................................................................100 6-9 Die photograph of the 5GHz monitoring system chip. ..........................................100 7-1 Bonding diagram of the 5 GHz chip. .....................................................................105 7-2 Transmitter output spectrum. .................................................................................105 7-3 Sketch of multiple targets monitoring system using phased array antenna. ..........106 7-4 An example of a two-band system. ........................................................................107 A-1 Transmitted and received signal spectra. ...............................................................108 A-2 Functional radar block diagram. .............................................................................110 A-3 Range correlation filter effects. ..............................................................................112 A-4 IF amplitude and phase noise spectr a – without range correlation effects. ............112 A-5 IF amplitude and phase noise spectra – with range correlation effects. .................113 xi

PAGE 12

Abstract of Dissertation Pres ented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy LOW-POWER RADAR SYSTEM FOR REMOTE DETECTION OF HEARTBEAT AND RESPIRATION USING DOUBLESIDEBAND TRANSMISSION AND FREQUENCY-TUNING TECHNIQUE By Yanming Xiao May 2007 Chair: Jenshan Lin Major Department: Electrical and Computer Engineering Since the 1970s, microwave Doppler radar ha s received more atte ntion as a remote monitoring system on human h ealth-care and life-sign monito ring and detection, such as physiologic movement and volume change sensing, life detection for finding human subjects trapped in earthquake rubble, ca rdiopulmonary monitoring for sleep apnea syndrome detection and hu man vital activities. This dissertation is concen trated on the theory study, design, implementation, and measurement of the radar vital sign monitoring systems. First, challenges and limitations occurring in the realization of the vita l sign monitoring systems are discussed and analyzed. It is proved that the double-side band transmission with frequency tuning technique is a good and simple solution to resolve the null point pr oblem and DC offset simultaneously. It is also show n that the harmonics of respir ation signal occu rring at high frequency may interfere with the detection of heartbeat and thus reduce its accuracy. xii

PAGE 13

After that, the first Ka-band vital sign monitoring system adopting double-sideband transmission and frequency-tuning technique is illustrated. This sy stem is built with discrete RF building blocks. This Ka-band sy stem has been demonstrated the ability to detect heartbeat and respira tion signal from a human body’s four different sides and shown sufficiently high detection accuracy of over 80% at up to 2.5-m distance. Except heartbeat and respiration detection, acoustic signal has also been successfully detected by the Ka-band system. In addition, this Ka-band system demonstrated the robustness in detecting the vital sign through a thick wood board. A portable non-contact vital sign monito ring system using 5 GHz radar is implemented for field test. The system achie ved better than 80% detection accuracy at 2.8 m distance with low transmission power. The radar module and the data acquisition module are both powered by the laptop through USB connection. Meantime, by comparing three different architectures us ed for the 5 GHz modules, double-sideband indirect-conversion architecture showed prominent advantag es over the direct-conversion architecture. Based on the above systems, an integrated monitoring system on silicon working at 5 GHz is designed. This integrated syst em adopts the double-sideband transmission architecture. The whole system is still on testing. For compar ison, some simulation results are given for reference. xiii

PAGE 14

CHAPTER 1 INTRODUCTION Microwave Doppler radar has been used for wireless se nsor applications for many years. Most common applicati ons include weather sensing [1] , position and distance sensing [2] , and automobile speed sensing [3] . Since the 1970s, microwave Doppler radar has received more attention as a non-contact vital sign measurement and detection system on human health-care, such as physiologic movement and volume change sensing [4] , life detection for finding human subject s trapped in earthquake rubble [5] , cardiopulmonary monitoring for sleep apnea syndrome de tection and human vital activities [6] – [8] . Obstructive sleep apnea syndrome (OSAS) affects 4% of all adult males and has many symptoms, including hypertension, ps ychological distress, and cognitive impairment. Although rates of sudden infant death syndrome (SIDS) have declined sharply in the past ten years, SIDS is still the third leading cause of infant mortality, and many more infants suffer from apnea. Mi crowave Doppler monitoring offers a noncontact alternative to commonly prescribed chest-strap monitors and, therefore, may provide a less intrusive option [8] . 1.1 Working Methodology Doppler radar vital-sign monitoring system typically transmits a continuous-wave (CW) signal, which is reflected off a target and then demodulated in the receiver. According to the Doppler theory, a target with a time varying position, but a net zero velocity, will reflect the si gnal with its phase modulated proportionally to the timevarying target position. For example, CW radar with the chest-wall as the target will 1

PAGE 15

2 receive a signal similar to the transmitted si gnal but with its phase modulated by the timevarying chest-wall position. If the heartbeat and respiration signals are to be monitored, demodulating the phase will then give a signa l proportional to the chest-wall position that contains information about movement due to heartbeat and respiration, from which heart and respiration rates and signatures can be determined. Base d on this principle, a noncontact heartbeat a nd respiration monito r can be envisioned [8] . The signal flow of the vital sign monitoring system is shown in Figure 1-1 . d x (t ) )( t T (t ) R (t ) d x (t ) )( t T (t ) R (t ) (a) (b) B ( t ) T ( t ) R ( t ) Figure 1-1. Signal flow of vital sign monitoring system. (a). T ( t ) is the transmitting signal; R ( t ) is the reflected signal; )( t is the phase difference between T ( t ) and R ( t ); d is the distance between the radar and the target. (b). The reflected signal R ( t ) is downconverted to B ( t ) by mixing with T ( t ). Assuming the CW transmitted signal T ( t ) in Figure 1-1 is a sinusoidal wave and has frequency component f , then )(2cos)( tfttT (1.1) where )( t is the total phase noise from the signa l sources and other building blocks in the transmitter. When the signal T ( t ) is reflected back by a target (human body), which has a timevarying chest-wall motion given by x ( t ), at a distance d, the total distance traveled between the transmitter and the receiver is 2 d ( t ) = 2 d + 2 x ( t ). According to [8] , the received signal can be approximated as

PAGE 16

3 ) 2 ( )(44 2cos)( c d t txd ft tR (1.2) where c is the signal’s propagation velo city (the speed of light), is the signal’s wavelength in air, which equals to c/f. ) 2 ( c d t represents the phase noise due to the effect of the medium noise and the original source phase noise. The received signal is similar to the transmitted signal, but has a time delay determined by the distance of the target an d a phase modulation due to the periodic motion of the target. The information of the periodic chest-wall motion can be demodulated and retrieved if this signal is mu ltiplied by a local oscillator (LO) signal that is derived from the same sources as the transmitted signal. This radar topology takes advantage of the ability to use the same oscillator for the transmitter and receiver, which keeps the phase noise of the two signals correlated. The resulting baseband signal B ( t ) is approximated as [8] )( )(4 cos)( t tx tB (1.3) 04 d (1.4) ) 2 ()()( c d ttt (1.5) where 4 d/ is the constant phase shift due to the distance to the target d, and 0 is a fixed phase shift due to the reflection at su rface and delays between building blocks. )( t represents the residual phase noise.

PAGE 17

4 Up to this point, the baseband signal B ( t ) turns out a cosine function of 4 x ( t )/ with and )( t as phase. In order to retrieve the wanted chest-wall motion x ( t ) accurately, the interference of , which is related with distance d, residual phase noise )( t , which is related to the LO source phase noise and environment clutter noise, and harmonic distortion, which is related to the nonl inear cosine transfer function, have to be considered carefully and comprehensively during the system design. 1.2 Chest-Wall Motion due to Heartbeat and Respiration The out-of-plane chest-wall displacement due to the heartbeat and respiration has been simply represented by x ( t ) in the above equations. Howe ver, as the heart and lung undergo complex movements within the thorax, the different cardiac structures exhibits varied activities, the displacements due to which are transmitted onto the chest-wall, which are shown with different amplitude and phase at different areas of the chest-wall surface. Therefore, it is too complicated to c onstruct a precise model to depict a people’s chest-wall motion. Nevertheless, for monitoring purpose, it is not necessary to know the accurate amplitude and phase of the displacement at different chest-wall areas, because what we are more interested in is to monitor whether the subject’s heartbeat and breathing rate is normal or not from the periodicity of the chest-wall motion. Therefore, without loss of generality, the chest-wall motion due to the heartbeat and respiration can be represented as the addition of two simple sinusoid waves with heartb eat and respiration rates as frequencies, respectively. For example, an ordinary man breathes about 18 times per minute, which is corresponding to the ches t-wall motion with frequency of 0.3.4 Hz. Meanwhile, when a man has 60 times per mi nute for heartbeat, then the chest-wall

PAGE 18

5 moves with the frequency of 1.5 Hz. Thes e two signals and the overall chest-wall displacement x ( t ) are written as )2sin()( tfmtxr r r (1.6) )2sin()( tfmtxh h h (1.7) )()()( txtxtxh r (1.8) where x r ( t ) represents the chest-wall displacement due to respiration, m r is the amplitude of the displacement, and f r is the respiration freque ncy (0.2.6 Hz). Similarly, x h ( t ) represents the chest-wall disp lacement due to heartbeat, m h is the amplitude of the displacement, and f h is the heartbeat fr equency (0.7 Hz). Normally, the amplitude m r is much greater than (sometimes more than 10 times) m h , and the frequency f r is 1/3 or 1/4 of f h . Therefore, when x r ( t ) is large enough, the baseband signal can not be approximated as a linear function of it any more, and strong high order harmonics will be appeared. Moreover, its third and fourth order harmonics happen to be around the heartbeat frequency, they are easy to block the heartbeat signal, and thus degrade the heartbeat detection accuracy. 1.3 History Microwave Doppler radar was first applied to the measur ement of respiration rate and the detection of apnea in 1975 [9] . Starting in the early 1980s , similar systems were proposed to search for vict ims trapped in earthquake rubble or an avalanche [5] and to sense human presence behind a wall or other barrier [10] . After that, a ultra-wideband (UWB) radar used for detecting similar hum an vital activities like heartbeat and respiration with very low power was proposed in 2002 [11] . All of these systems were built with bulky heavy microwave components, which are acceptable for use in

PAGE 19

6 diagnostic or emergency situations, but ar e impractical for everyday home monitoring. Therefore, a single-chip monitoring system should substitute to provide a more flexible non-contact alternative. In 2001, a chipset working at 2.4 GHz wa s presented to be capable of detecting the vital sign successfully at about 0.5 m distance [6] – [8] . Although all of these systems have been demonstrated the capability of det ecting the vital sign remotely, more or less, further improvement is still necessary. Microwave life-detection syst em that could be used to locate human victims trapped deep under earthquake rubble or collap sed building debris wa s illustrated by the Michigan State Universi ty as early as 1980s [5] . They built three different operating frequencies’ system at L-, S-, and X-band for different ma terials and penetration depth applications. These system are quite compli cated except the basic RF components, they contain a microprocessor-controlled clutter cancellation system which creates an optimal signal to cancel the clutte r from the rubble and the background and alleviate the null point problem, and a dual-antenna system whic h is used to receive two reflected signals simultaneously and then extract the respirati on and heartbeat signals by cross-correlating these two signals to eliminate noise interf erence. An 1150-MHz micr owave life-detection system of the Michigan State University is shown in Figure 1-2 [5] . This system uses a simple signal pr ocessing method by applying Fast Fourier Transform (FFT) to the detected signal to search for the respiration and heartbeat signals on the frequency spectrum, and then assuming that the peak around 0.3 Hz is the respiration signal component and the peak aroun d 1 Hz is the heartbeat signal. However, the 3 rd or 4 th order harmonic of respiration signal is around 1 Hz too, when it is strong, the heartbeat signal is completely blocked. Th erefore, the heartbeat signal obtained on the

PAGE 20

7 frequency spectrum is probably not the real heartbeat signal, but the harmonics of the respiration signal instead. The detection accuracy is not evaluated quantitatively in these systems too. Figure 1-2. Block diagram of a1150-MHz microwave lif e-detection system [5]. A novel I/Q architecture used in a dire ct-conversion motion-sensing system to eliminate the null point problem, which was demonstrated by the Stanford University [6] – [8] in 2001, has been successful realized in th e chip level. This architecture is much simpler than that illustrated in [5] . This system adopts I/Q demodulator to obtain two baseband signals which are in quadurature, thus guarantee at least one signal will not at the null point according to the definition of the null point and optimum point [8] . Therefore, at least one baseband signal can give high detection accuracy. The system achieved 100% detection accuracy from one channel (optimum point) while 46% from the other one (null point). The schematic of this I/Q demodulator is shown in Figure 1-3

PAGE 21

8 [8] . However, this system has a large DC offset problem, which is hard to be filtered out because the wanted signal (0.2 Hz) is very close to DC. Moreover, adopting separate I and Q channels, the baseband circuitry and the signal processing part will be doubled. How to combine two channels togeth er is still an awaiting issue. Figure 1-3. Block diagram of a 2.4-GHz chip-l evel vital-sign monitoring system [8]. In contrast to CW radar, ultra-wideband (UWB) radar, which was proposed for detecting human vital activities in 2002, transmits repetitive short pulses in time and receives the reflected version of it [11] . The motion of the target changes the repetition frequency of the reflected wave. The UWB radar approach does not show any null point problem up to now. However, a time discrimina tor consisting of fast-acting switches is required to select the wanted reflected pulses and eliminate interfering pulses. A software-controlled delay line is used to c ontrol the gating, and the distance between the radar and object needs to be known in adva nce for the microcontroller to program the correct delay. If the distance changes, th e delay also needs to be changed. The UWB radar detection accuracy increases as the detection time increases, and it achieves more than 92% accuracy when the detection time is as long as 78-S. The schematic of UWB radar is shown in Figure 1-4 [11] .

PAGE 22

9 1.4 Proposed System with Double-Sideband Transmission Based on the summarized advantages and drawbacks of the above systems, a new monitoring system adopting an indirect-c onversion architecture with double-sideband transmission and frequency-tuning technique was proposed to compromise the above mentioned shortcomings. Figure 1-4. Block diagram of a UWB ra dar vital sign monitoring system [11]. Since in a direct-conversi on topology the downconverted signal extends to zero frequency, extraneous offset voltages can co rrupt the signal and saturate the following stages. DC offset mainly comes from the self -mixing of the LO signal due to the finite isolation between the LO port and the input s of the mixer and the LNA. The higher operating frequency, the lower isolation of the mixer and LNA tend to have. In microwave life-detection system [5] and 2.4-GHz I/Q demodulator system [6] – [8] , the baseband signal is directly downconverted fr om GHz signal, DC offset is unavoidably high. If using indirect-conversion topology, DC offset can be easily resolved because of the good RF-LO isolation of the second stage low-frequency mixer. This issue will be discussed more detailed in Chapter 2.

PAGE 23

10 Double-sideband transmission is also a solution to th e above mentioned null point problem, which is commonly existed in th e direct-conversion topology. As discussed above, microprocessor-controlled cl utter cancellati on system in [5] and I/Q demodulation in [6] – [8] are effective solutions to a certain exte nt, but the first one is too complicated and the second one has the channel co mbining issue. For the double-sideband transmission solution, double-sideband waves at the transmitter output are set to be in quadrature to overcome the null point problem by selecting proper frequency separation between them. In addition, when the two transmitted waves result in a null-point condition in the measurement, this null point can be easily removed by slightly adjusting the second stage IF frequency. This solution is simple and easy to be realized comparing to those in [5] – [8] . The detailed working methodology will be discussed in Chapter 2. Both I/Q quadrature receiver method and the double-sideband transmission method resolve the null-point issue. The I/Q quadrat ure receiver method has been demonstrated in monolithic integration with the benefit of no need of image-reject filter, the doublesideband transmission method with indirect-c onversion architecture also eliminates the need of image-reject filter and IF filter, a nd can be monolithically integrated as well. The double-sideband transmission method also eliminates the n eed of generating quadrature LO signals. As a result, the indirect-conve rsion architecture with double-sideband transmission is more feasible for the CW vital-sign monitoring system compared to the previous reported systems [5] – [9] [11] . 1.5 Organization This dissertation is mainly concentrated on the theory study, design, and implementation of Doppler radar vital-sign non-contact monitoring systems using double-sideband transmission and frequency-tuning technique.

PAGE 24

11 In Chapter 2, challenges and limitations occu rred in the realization of the vital-sign monitoring system are discussed and an alyzed. The double-sideband transmission approach and frequency tuning technique are introduced with detailed analysis. It is proved that this approach is a good and simple solution to resolve all challenges together. It will also be shown that the third or fourth harmonics of respiration signal may interfere with the detection of heartbea t and thus reduce its accuracy. In Chapter 3, the system architecture and design consideration about RF transceiver, antennas, baseband circuitry, and signal proce ssing section are discussed. The concepts of minimum detectable signal of the radar and th e receiver sensitivity are discussed in this chapter too. In Chapter 4, the first vital sign m onitoring system adopting double-sideband transmission and frequency-tuning technique is illustrated. This sy stem is built with discrete RF building blocks and worked at Ka-band. Except the system description, excellent detection re sults measured under different condi tions are presented as well. In Chapter 5, 5-GHz portable modules bui lt on boards for vital sign sensing are demonstrated in three different architectures. By comparing the measurement data, the indirect-conversion architecture with double-sideband transmission is further proved to be a simple and effective way to overcome all challenges. Based on the above systems, in Chap ter 6, a double-sideband transmission monitoring system working at 5 GHz is designed on silicon. At this stage, the schematic of each block and simulated results are presented. Also, the whole system simulation results are given for reference. In Chapter 7, except a summary, suggested future work will be given as well.

PAGE 25

12 CHAPTER 2 LIMITATIONS AND DOUBLE-SIDEBAND TRANSMISSION As discussed in Chapter 1, Using Doppler eff ect to detect and m onitor the vital sign of human beings and animals has aroused popular interest since 1970s. However, up to now, research on this area is still on going. Not a system previously reported shows the capability of stable long-term monitoring [4] – [11] . What is expected for a feasible noncontact vital-sign monitoring system? Accurate, stable, long-term, low power and convinced detection should be most desi red. Therefore, what limits the above performance to be realized? By comparing the previously re ported systems and our system [4] – [11] [16] – [18] [28] , clutter noise and signal pha se noise, DC offset, null point, high-order harmonics shown in Figure 2-1 are four main challenges encounter ed thus far, either one or the multiple combination of which could greatl y degrade the whole system performance. Except DC offset, the other three challenges are related to the baseband equation (1.3). How they affect the system performance and relevant solutions will be elaborated in details in the following sections. DC Offset Null Point High-Order Harmonics Radar Senso r Clutter Noise Phase Noise Figure 2-1. Four limitations in vital sign monitoring system design.

PAGE 26

13 2.1 Phase Noise and Clutter Noise As discussed in Chapter 1, the periodic chest-wall movement was encoded as a phase modulation in the received signal and indicated as 4 x ( t )/ . The unwanted clutter echoes reflected from the surrounding environm ent, such as wall, door, chair, and human body account for part of the residual noise ( t ) in (1.3). Clutter is the term used by radar engi neers to denote unwanted echoes from the natural environment. It implies that these unwanted echoes “clutter” the radar and make difficult the detection of wanted targets. Clutter includes echoes from land, sea, weather, birds, and insects. Clutter is generally distributed in spatial extent in that it is much larger in physical size than the radar resolution cell. Large clutter echoes can mask echoes from desired targets and limit radar capability. It is well known that the performance of CW Doppler radar in the presence of clutter is limited by the phase and amplitude modulation noise sidebands of the local oscillator (LO) signal used to generate th e transmitted signal and convert the received signal to some intermediate frequency (IF). The net effect of the noise sidebands is to spread clutter energy into the frequency re gion of the target signal and potentially obscure the target return or, at least, reduce the target signal-to-clutter (SK) ratio. The transmitted and received signal spectra are illustrated in Figure 2-2 , in which, f o is the carrier frequency and f d is the target Doppler frequency. It is assumed that the clutter is at zero Doppler [12] [13] . Since the heartbeat and respiration informa tion is encoded in the phase modulations and has the frequency of 0.1 Hz, where the pha se noise is near its peak, the wanted signal will be nearly buried by the phase noise as illustrated in Figure 2-2 (d). However, when the same LO source is used for tran smitting and receiving, the phase noise of the

PAGE 27

14 received signal is correlated with that of LO, with the level of correlation dependent on the time delay between two signals. When the dela y is small, this effect greatly decreases the noise spectrum at baseband. The time delay is proportional to the target range (distance between the radar and the target); hence, this phase noise reducing effect is known as range correlation eff ect. For details, see Appendix. fofofo+ fd fofofo+ fdClutte r Tar g et Clutte r Tar g et (a) (b) (c) (d) Figure 2-2. Transmitted and received signal spectra. (a) ideal transmitted signal, (b) received signal associated with ideal transmitted signal, (c) “practical” transmitted signal that includes noise sidebands, (d) received signal associated with “practical” transmitted signal. More specifically, according to [13] , with the target at a given range R , the baseband noise spectral de nsity at offset frequency is wr itten as follows in (2.1), where the RF phase-noise density is : )(ofS )2(sin4)()(2c Rf fSfSo o o (2.1) At values relevant for radar m onitoring of heart and respiration, Rf o / c will be on the order of 10 -9 , so the small-angle approximation is va lid and range correl ation will cause the baseband noise spectrum to increase proportionally to the square of the target range R and the square of the offset frequency f o : 2 2 2 216)()( c fR fSfSo o o (2.2) For example, with a 50-cm range and an offset frequency of 1 Hz, the value of Rf o / c is 1.67x10 -9 . The error due to the small-angle a pproximation at this point is near 10 -60 .

PAGE 28

15 The resulting baseband phase noise at 1 Hz is decreased by 154 dB [8] . Range correlation has a much less significant effect on amp litude noise. For small and Gaussian white amplitude noise, it results in a gain of 3 dB [13] . Since, as shown in (1.3), the residual phase noise appears as additive noise on the baseband signal, the phase-noise reduction due to the range-correlation eff ect is particularly important. If two differen t oscillators with uncorrelated phase noise were used for transmitting and receiving, it would be impossible to detect the small phase varia tions created by heart and respiration motion [8] . Therefore, the range correlation effect o ffers a big advantage for the close-to-DC heartbeat and respiration si gnals’ detection at baseband. 2.2 DC Offset Because of the LO leakage between the LO port and the input of mixer, DC offset is easily produced by self-mixi ng of LO signal in the mixer [14] . The higher operating frequency, the lower isolati on the mixer tends to be. Di rect-conversion architecture converts the RF signal directly to baseband; LO leakage will cause a big DC voltage at baseband. Figure 2-3. Relationship of DC offset and wanted signals. Wanted Signal DC Offset 0.2Hz 2Hz Filter DC offset is very critical for this vita l sign monitoring system, because the wanted signal is located from 0.1 Hz to 2 Hz in the spectrum of baseband, which is very close to DC voltage. Figure 2-3 shows the relationship of DC offs et and the wanted signals. It is

PAGE 29

16 difficult to filter this DC offset out by us ing the traditional filter without reducing the wanted signal strength, because the wanted si gnal is too close to DC. Therefore, DC offset should be kept as low as possible. To prevent the amplified DC offset vo ltage from exceeding the following data acquisition (DAQ) module dynamic range, an au tomatic gain control (AGC) circuit has to be used before the DAQ module. Larger th e DC offset, lower the AGC gain, lower the wanted signal amplitude. Therefore, too high DC offset will degrade the bandband signalto-noise ration (SNR), and thus desensitize the wanted signals. I ndirect-conversion adopts two-stage down-conversion; the frequency of the second stage is normally as low as MHz, which is very easy to obtain a high-isola tion mixer at this fre quency. Therefore, the DC offset voltage of the indirect-conversion architecture is much less than that of its direct-conversion counterpart. To reduce DC offset, indire ct-conversion architecture is superior to the direct-conversion one. 2.3 Null Point and Optimum Point Direct-conversion architectur e, which was often adopted in the Doppler radar detection system in the past [4] – [9] , has the advantage of the simplest architecture with single-tone transmission and one-step co nversion. However, direct-conversion architecture not only has a severe DC offset voltage that could saturate the following baseband circuits, but also has an unavoida ble null point problem, which could severely degrade the detection reliability at high frequency. 2.3.1 Single-Tone Transmission As discussed in Chapter 1, the baseband signal B ( t ) after down-conversion is approximated as

PAGE 30

17 )( )(4 4 cos)(0t tx d tB (2.3) where 0 is the constant phase shift due to surface reflection and delay between blocks. Its existence does not affect the null point distribution that we are interested in. Therefore, without loss of generality, 0 will be ignored in the following discussion, and the baseband signal will be rewritten as )( )(44 cos)( t txd tB (2.4) When 4d/ in (2.4) is an odd multiple of /2, the small-angle approximation is valid if x(t) is much less than wavelength [19] , and the baseband output is approximately )( )(4 )( t tx tB (2.5) In this case, the baseband output is linearly proportional to the periodic chest-wall movement x(t) summed with the phase noise )( t , and the optimum phasedemodulation sensitivity is achieved. We call it the optimum point . The distance d opt where optimum points occur and the separation d opt between two nearest optimum points will be: 4 84 2 1 4 opt opt optd k d k d (2.6) When 4d/ in (2.4) is an integer multiple of , the baseband output is approximately 2)( )(4 1)( t tx tB (2.7)

PAGE 31

18 In this case, the baseband output is no longer linearly proportional to x(t) , but proportional to the second order harmonic of x ( t ). The fundamental component of x ( t ) is disappeared, thus the sensitivity is decreased. We call it the null point. The distance d null where null points occur and the separation d null between two nearest null points will be: 4 4 4 null null nulld k dk d (2.8) Therefore, the optimum point occurs with a target distance every /4 from the radar, and so does the null point. Subtracting (2.6) by (2.8), the distance between the adjacent null point and optimum point d o n will be: 8 null optnoddd (2.9) The null points and optimum point s are distributed alternat ely and the adjacent null point and optimum point are separated by /8. Figure 2-4 shows the distribution of null points and optimum points along the path fr om the radar to the subject for a single sideband transmitted wave. /8 d1 Optimum Point Null Point Antenna /8 /8 /8 d2d3d4d d5 Figure 2-4. Optimum points and null points distribute al ong the path away from the radar. d 1 , d 3 , and d 5 are optimum points. d 2 and d 4 are null points. The adjacent null point and optimum point are separated by /8. When 4d/ in (2.4) is an ar bitrary value between /2 and , using Taylor expansion, the baseband signal will be com posed of the fundamental signal and higher

PAGE 32

19 order harmonics. As long as x ( t ) << , the fundamental term is mu ch larger than the high order term, and the heartbeat signal can s till be detected. However, the detection sensitivity will be betw een the above two cases. For a microwave signal at 27 GHz, the dist ance between the adjacent null point and optimum point is only 1.39 mm ( /8). This distance is about in the range of the chest-wall movement, that means, during the time of chest-wall moving back and forth, both the null point and optimum point might be encounter ed in one period, thus a continuous and reliable detection is difficult to achieve. To overcome this problem, one effective solution is quadrature demodulation as shown in Figure 2-5 . 0 90 BI(t ) BQ(t ) T (t ) R (t ) Figure 2-5. Block diagram of a quadrature demodulation. The LO signal T ( t ) is divided into two, with 90 o phase difference. When these two signals are mixed with R ( t ), the resulting baseband signals B B I ( t ) and BQ B ( t ) will have 90 o phase difference too. When one signal, for instance, B B I ( t ), is detected from a null point d null and thus mainly showing the second harmonics; the other one BQ B ( t ), which has 90 o phase difference from B B I ( t ), will give the optimum detecti on sensitivity of the heartbeat and respiration signals even for the same d null . This approach can gua rantee at least one signal will not give the null point problem, thus high detection accuracy can always be achieved.

PAGE 33

20 However, as discussed above, the distan ce between the null poi nt and the optimum point is so small in the high frequency that a reliable detection is difficult to achieve. Other than the unreliable issue, the DC offset is also a problem existed in the quadrature demodulation. To realize a reliable detecti on, a double-sideband transmission approach is proposed to solve this probl em and has less DC offset [17] . 2.3.2 Double Sideband Transmission As discussed above, if the radar just transmits a singl e-tone wave, the detection accuracy varies dramatically with even a ve ry small movement of the subject, making it extremely difficult to achieve reliable detection accuracy under this condition. When the separation between the null point and the optimu m point is in the range of the chest-wall movement amplitude, the unreliabl e issue is even worse. Ther efore, this radar monitoring system cannot work properly at higher frequency if it transmits only a single-tone wave. Fortunately, this problem can be solved by taking the advantage of double sideband transmission. A general block diagram of an indirect-conversion transcei ver used for th is analysis is shown in Figure 2-6 . This architecture includes onl y one mixer (Mixer3) in the transmitter path, and one LNA, one RF mixer (Mixer1), one IF amplifier (IFamp), one IF mixer (Mixer2) in the receive r path. Two LO sources, one provides RF signal (LO2), and the other one provides IF signa l (LO1). Two power splitters are used to split two LO signals into two and feed them to the mixers in the transmitter and receiver, respectively. Since only phase modulation is considered, without lost of generality, amplitude variations are neglected and thus two LO signals S 1 ( t ) and S 2 ( t ) are written as ))(2cos()(11 1ttftS (2.10)

PAGE 34

21 ))(2cos()(22 2ttftS (2.11) where f 1 and f 2 are frequencies of S 1 ( t ) and S 2 ( t ), respectively, t is the elapsed time, and 1 ( t ), 2 ( t ) are phase noises of S 1 ( t ) and S 2 ( t ), respectively. Mixer3 LNA Mixe r 1 IFamp Mixer2 Splitter1 Splitter2 LO2 ( f2) B (t ) LO1 ( f1) T (t ) R (t ) Figure 2-6. General block diagram of an indirect -conversion architecture. Since there is no filter following Mixer3, the output T ( t ) of Mixer3 has two main frequency components: lower sideband f L = f 2 – f 1 and upper sideband f U = f 2 + f 1 . The received signal R ( t ) includes these two frequency components f L and f U as well. For either one of these two sideband signals , equation (2.3) is still valid. Let B B L ( t ) and BU B ( t ) represent the baseband signals corresponding to f L and f U , respectively. In this case, )()()( tBtBtBU L (2.12) )( )(4 cos)( t tx tBL L L L (2.13) )( )(4 cos)( t tx tBU U U U (2.14) and U U UL L Ld d0 0 0 04 , 4 (2.15)

PAGE 35

22 where L and U are wavelengths of lower sideband and upper sideband, which equal to c/f L and c/f U , respectively. L and U are fixed phase shifts of the lower sideband signal and the upper sideband signal, respectively. 2.3.2.1 Double sideband As known from the single-tone wave case, either B B L ( t ) or BU B ( t ) has the severe null point problem and cannot give a reliable detection at hi gh frequency. However, when B B L ( t ) and BU B ( t ) simultaneously exist, B ( t ) is the superposition of B B L ( t ) and BU B ( t ). B B L ( t ) and BU B ( t ) are similar but with a phase difference between them. If their phase difference is arranged properly, the baseband output B ( t ) might not have the severe null-point problem as either B B L ( t ) or BU B ( t ) alone. Figure 2-7 shows the distribution of null points and optimum points for double sideband transmission. d L/8 dL5 Antenna dL1dL2dL3dL4 d dU 5dU 1dU 2dU 3dU 4 U/8 U/8 U/8 U/8 L/8 L/8 L/8 Figure 2-7. Optimum points and null points di stribute along the path away from the radar for double sideband transmission. The subs cript L represents lower sideband, and U represents upper sideband. If the frequency of the double sideband is arranged properly, th e null points from lower sideband and optimum points from upper sideband, or vice versa, can overlap each other. Good detection accuracy is theref ore achieved over a wide distance range. Since the residual phase noises L ( t ) and U ( t ) in (2.13) and (2.14) are much smaller compared to and the phase modulation 4 x ( t )/ , due to the effect of range

PAGE 36

23 correlation, their effect will be ignored in the following analysis. In addition, phase modulations 4 x ( t )/ L and 4x ( t )/ U are small angle, they have nearly the same amplitudes because L is very close to U . Next, we will discuss how the null point changes versus the relationship of L and U in four cases. Case 1: When L and U are separated by an even multiple of , B B L ( t ) and BU B ( t ) are in-phase and synchronized. )(2 )( )(4 cos)( )(4 cos )( )(4 2cos)( )(4 cos)( tB t tx t tx t tx kt tx tBL U U L L L L U U L L L L (2.16) Therefore, except for giving nearly double amplitude, B ( t ) will give almost the same optimum points and null points at the same places as those given by either B B L ( t ) or BU B ( t ) alone, and has the same problem of closely spaced null points that degrade the detection accuracy and reliability. Case 2: When L and U are separated by an odd multiple of , B B L ( t ) and BU B ( t ) are out of phase. Since B B L ( t ) and BU B ( t ) have almost the same amplitudes but with an opposite phase, they will cancel each other to a certain extent. 0 )( )(4 cos)( )(4 cos )( )(4 )12(cos)( )(4 cos)( t tx t tx t tx k t tx tBU U L L L L U U L L L L (2.17) Therefore, the amplitude of B ( t ) is very small and hard to be detected. This case can also be illustrated by a simulation results shown in Figure 2-8 .

PAGE 37

24 B (t ) BL(t ) BU(t ) Figure 2-8. Case of L and U separated by an odd multiple of . B ( t ) (red line) is the addition of B B L ( t ) (black line) and BU B ( t ) (blue line). Summing up the above two cases, wh en the phase difference between L and U is the integer of , a new null-point condition occurs in the measurement. If the null point of the single sideband transmission is defined as the local null point , then this new null point condition is defined as the global null point . At this global null point, the detection accuracy is the lowest. Let ,...2,1,0, 440 kk ddL U LU (2.18) where L U 0 00 (2.19) Substituting L = c/f L , U = c/f U , then ,...2,1,0),( 40 k k d c ffLU (2.20) Substituting f U = f 2 + f 1 , and f L = f 2 – f 1 in (2.20), then

PAGE 38

25 ,...2,1,0, 8 5.370 1 k d c MHz d k f (2.21) where d is the distance in meter. Equati on (2.21) shows the relationship of f 1 and d when a global null point occurs. At a fixed distance d, if LO1 frequency is set to th e values as indicated in (2.21), then the phase difference between L and U is always the integer of , then the location at d will always be a global null point. The frequency step for the nearest global null point is MHz d fnullG5.37 1 (2.22) For another situation, if LO1 frequency f 1 is fixed, rewriting (2.21) as ,...2,1,0, 880 1 1k k dnullG (2.23) where d Gnull represents the location of the global null point, and 1 = c 1 / f 1 . Therefore, the global null point will be distributed along the path from the radar to the target periodically similar to the single-tone transmission. Howeve r, the distance between the nearest global null points at th is time has been changed to 18 1 nullGd (2.24) Normally, 1 is much larger than 2 , thus the distance of the adjacent null points will be enlarged greatly. That is one of benefits of this double sideband transmission architecture. Case 3: When L and U are separated by an odd multiple of /2, B B L ( t ) and BU B ( t ) are in quadrature. For example, the baseband signal B ( t ) can be written as:

PAGE 39

26 )( )(4 sin)( )(4 cos )( )(4 2 2cos)( )(4 cos)( t tx t tx t tx kt tx tBU U L L L L U U L L L L (2.25) In this case, if one signal such as B B L ( t ) is at the null point, then BU B ( t ), which is quadrature to B B L ( t ), will be at the optimum point, or vi ce versa. Therefore, at least one of BL B ( t ) and B B U ( t ) is not at the null point, th e one that is not at the null point will determine the final output B ( t ). This case can be illustrated by . Figure 2-9 B (t ) BL(t ) BU(t ) Figure 2-9. Case of L and U separated by an odd multiple of /2. B ( t ) is the addition of B B L ( t ) (null point) and BU B ( t ) (optimum point). In this case, the overall detection accuracy will be high. This point is defined as the global optimum point . Let ,...2,1,0, 2 440 kk ddL U LU (2.26) Repeat the same process as in (2.20)-(2.21), ,...2,1,0, 8 75.18 120 1 k d c MHz d k f (2.27)

PAGE 40

27 where d is the distance in meter. Equati on (2.27) shows the relationship of f 1 and d when a global optimum point occurs. Similar to the global null point case di scussed above, at a fixed distance d, if LO1 frequency is set to the values as indicated in (2.27), then the phase difference between L and U is always the integer of /2, then the location at d will always be a global optimum point. The frequency step for the nearest optimum null point is MHz d foptG5.37 10 (2.28) and the optimum point distribution along the path from the radar to the subject is ,...2,1,0, 880 1 1k k doptG (2.29) where d Gopt represents the location of the globa l optimum point. The distance between the nearest global optimum points is equal to the global null point case 18 1 optGd (2.30) The frequency difference between f U and f L is 2 f 1 . Therefore, the selection of f 1 will determine if L and U are separated by k or k + /2, if the subject is seated at a null point or an optimum point, and how far the separation of the null point and optimum point. Case 4: When L and U are separated by an arbi trary angle other than k and k + /2, or f 1 frequency is between the above two cas es, the detection accuracy will be between the above two cases. Th is condition is illustrated in Figure 2-10 . The above analysis shows that when the position of the subject is fixed, this position can be set to a global optimum point or a global nu ll point by properly choosing

PAGE 41

28 the f 1 frequency. Also, the frequency tuning step between the null point and optimum point can be obtained by s ubtracting (2.21) by (2.27): B (t ) BL(t ) BU(t ) Figure 2-10. Case of L and U separated by by an arbitrary angle other than k and k + /2. B ( t ) is the addition of B B L ( t ) and BU B ( t ). The above analysis shows that when the position of the subject is fixed, this position can be set to a global optimum point or a global nu ll point by properly choosing the f 1 frequency. Also, the frequency tuning step between the null point and optimum point can be obtained by s ubtracting (2.21) by (2.27): MHz d k fnulloptG75.18 )12(0 (2.31) The least frequency step betw een the null point and the optim um point is 18.75 MHz. For example, if at a given f 1 frequency, the subject position at d = 1-m happens to be a null point, this null point can be ch anged to an optimum point if f 1 is tuned to f 1 18.75MHz according to (2.31). This means that an accurate detection can always be made at an optimum point by adjusting f 1 without moving the subject’s position.

PAGE 42

29 When the frequency f 1 is fixed, the distribution of the global null points and optimum points for double sideband transmissi on is similar to the single sideband case but the distance is enlarged due to the super position of two baseband signals. Subtracting (2.23) by (2.29), the distance between the global null point and global optimum point can be obtained as 16 12 k doptnullG (2.32) From equations (2.23) and (2.29), the global null points are encountered every 1 /8, so are the global optimum points. Furthermore, ad jacent global null point and global optimum point are separated by 1 /16 according to (2.32). The distribution of the global null points and the global optimum poi nts for double sideband transmission is shown in Figure 2-11 . 1/16 d1Antenna 1/16 d2d3d Figure 2-11. Global Optimum points and null points distribute for double sideband transmission along the path away from the radar. d 1 and d 3 are optimum points. d 2 is null point. The adjacent global null point and optimum point are separated by 1 /16. Since the LO1 frequency f 1 is much smaller than the LO2 frequency f 2 , the distance between adjacent global null point and global optimum point is much larger than the single sideband case. For f 1 = 500-MHz, which is much smaller than any Ka-band frequency, the null point occurs every 75-mm. This is five times larger than the null point separation of 15-mm for a si ngle 5-GHz wave. Therefor e, by using double sideband transmission, it is possible to obtain reliable detection accu racy and avoid the null point problem by adjusting the position of the radar.

PAGE 43

30 2.3.2.2 Frequency tuning technique As discussed above, when the distance is fi xed, the null point can be eliminated by ertain value. The distribution of null points and optim ts distribute versus both distance and From (2.23), it seems that the lower the f1 frequency, the further are the null points 1when tuning the LO1 frequency f 1 by a c um points versus both dist ance and frequency is shown in Figure 2-12 . Figure 2-12. Global null points and optimum poin frequency. d and f are two variables. separated and thus the null point probl em would be solved with very low f . However, the f 1 frequency is too small, the null poin ts will be dominated by the local null points over a wide range in distance. Figure 2-13 shows the distribution of the local null points and the globa l null points for f 2 = 27.1-GHz and f 1 = 500-MHz, 50-MHz, and 5MHz, respectively. The y-axis indicates the normalized amplitude of the signals. When the signal hits the valley, the amplitude is th e smallest, thus the de tection accuracy is the lowest. The light solid and the light dotted li nes show the distribution of the local null points and the local optimum points for baseband signals B B L ( t ) and BU B ( t ) respectively. The amplitude of B B L ( t ) and BU Bd f1 f1 f3 f3 ( t ) may have a little differe nce because of frequency response flatness in transceiver, but here the same amplitude is assumed for the convenience of analysis. d1d2d3 Radar f f2 f2

PAGE 44

31 As shown in Figure 2-13 , the separation of nearest lo cal null points (valley) is about 2.5-mm. The thick solid lines shows th e distribution of the global null points and the gl obal optimum points for B ( t ). When f 1 = 500-MHz, the separation of the global null points is 75-mm, which is shown in Figure 2-13 (a). However, for f 1 = 5-MHz, the separation of the global null poi nts is 7.5-m. As shown in Figure 2-13 (c), within a 0.1-m range, B (t) has the same null points and optimum points as those of B B L ( t ) or BU B ( t ), which was qualitatively defined as a global null point in previous analysis. Quantitatively, if the signal valley amplitude for B ( t ) falls under 20% of peak amplitude of either B B L ( t ) or BU Brement at or near the optimum point by either 1). Howe ( t ), then we define this condition as the global null point region . By this definition, B ( t ) will stay in a global null point region for about 1-m long for f 1 = 5-MHz, 0.1-m for 50-MHz, and 0.01-m for 500MHz, respectively. To overcome the null point problem in the measurement, and to obtain high detection accuracy, it is better to make the measu moving the radar position or changing the f 1 frequency. For f 1 as low as 5-MHz, sometimes it is hard to move the system as much as 3-m in distance for it to reach a nearest optimum point. Therefore, the best way is to adjust the LO1 frequency f 1 . If a null point occurs at d = 2.5-m, in order to switch th is null point to an optimum point, the f 1 frequency will need to be changed at least 7.5-MHz according to (2.3 ver, if a null point occurs at d = 0.1-m, the smallest tuning step will be 187.5-MHz, which is quite a large tuning range fo r LO1. Therefore, the selection of f 1 frequency and the VCO tuning range need to be considered together when the null point appears at a distance close to radar. Therefore, in th is system, a VCO with tuning range from 450MHz to 800-MHz was selected as f 1 source. At the same ti me, this VCO frequency

PAGE 45

32 provides about 75-mm null point se paration, so it also provides a possibility to avoid the null point by adjusting the Radar position [17] . Figure 2-13. The distribution of null points (global and local) with different LO1 frequency f1. (a) f1=500-MHz (b) f1=50-MHz (c) f1=5-MHz. The dashed line indicates 20% amplitude. ecause the chest-wall movement is due to breathing and heartbeat, applying (1.8) to (1.3), the received base band signal can be represented as [18] : 2.4 Harmonic Distortion B

PAGE 46

33 4() 4 ()cos(hxt Bt () )rxt Normally, an ordinary people have a hear tbeat rate of a (2.32) bout 3~4 times of his respiration rate. Also, the amp litude of chest-wall movement due to respiration is more than 5 times that due to heartbeat. If 4 xr( t )/ is not greatly less th an one, equation (2.32) can n noise existed in the baseband signal can be alleviat ed by elation e ffect, which is reflected by using ot be expanded by the small-angle appr oximation any more. If the third order or fourth order harmonics generated by the resp iration signal, which exactly falls in the heartbeat frequency range, is stronger than the heartbeat sign al, the heartbeat signal will be desensitized. This will be illustrated more detailed in Chapter 4. 2.5 Summary In this chapter, we summarized the cha llenges and limitations encountered in the vital sign monitoring system design. Clutte r noise and phase the range corr the same LO source for the transmitter an d receiver. DC offset is critical for the close-to-DC vital sign detec tion, and the occurrence of th e null point can degrade the detection accuracy and stability. Both of them can be relieved by using indirectconversion architecture with double-side band transmission. A frequency-tuning technique can further be used to switch th e null point to the opt imum point, and thus improve the detection accuracy. The effect of high order harmonics of respiration signal on the heartbeat detection is another impor tant obstacle in improving the detection accuracy. The indirect-conversion architectu re with double-sideband transmission is a better and direct solution to resolve DC offset and null poi nt problem simultaneously up to now. Meanwhile, without using image reject filter, the indirect-c onversion architecture can easily be integrated on silicon.

PAGE 47

CHAPTER 3 SYSTEM ARCHITECTURES The whole vital sign monitoring syst em includes two antennas (Rx_Ant and Tx_Ant), RF section (RF Receiver and RF Transmitter), baseband section, and signal processing section as shown in Figure 3-1 . Figure 3-1. Block diagram of th e vital sign monitoring system. In Chapter 2, we have discussed the ch allenges and limitations in extracting the wanted heartbeat and respiration in formation from the baseband signal B ( t ). All these discussions were mainly based on an assumed ideal system, such as: receiver sensitivity is high enough; RF section has enough ba ndwidth to support double-sideband; and no other noise will be introduced in the baseband circuitry, etc. Therefore, how to build a system that meets these criteria will be the focus of this ch apter. We will start with the introduction of the radar range equation. 3.1 Radar Range Equation The analysis and design of rada r often require the use of the Friis Transmission Equation and the Radar Range Equation. The radar range equati on relates the range of radar to the characteristics of the transm itter, receiver, antenna, target, and the RF Receiver Baseband Section Signal Processing Section Tx_Ant Rx_Ant RF Transmitter RF Section 34

PAGE 48

35 environment. It is useful not only for determining the maximu m range at which particular radar can detect a target, but it can serv e as a means for understanding the factors affecting radar performance. It is also an design [20] . For polarization-match m directional radiation and recep important tool to aid in radar system ed antennas aligned for maximu tion, the radar range equation is written as [21] : 2 24 4 R Pt GG Prt r (3.1) where Pr: received power, W Pt: transmitted power, W Gt, Gr: antenna gain : signal wavelength in air, m Antenna is an importan es to place energy on target durin : radar cross section of the target, m 2 Except for the target’s radar cross section, the other parameters in this equation are under the consideration in the design. It st ates that if long ra nges are desired, the transmitted power should be large, the radiated energy should be concentrated into a narrow beam (large transmitting gain), the echo energy should be received by a large antenna aperture (also synonymous with large gain), and the receiver should be sensitive to weak signals [20] . 3.1.1 Antenna Gain G t part of this sy stem. It serv g transmission, collect the received echo energy reflected from the target. The antenna gain G is a measure of the power per unit solid angle radiated in a particular direction by a dire ctive antenna compared to the power per unit solid angel

PAGE 49

36 which would have radiated by an omni directio nal antenna with 100% e fficiency. It is the power gain accounting for losses within the ante nna and is a function of direction. If it is greater than unity in some directions, it mu st be less than unity in other directions. There is also the directive gain , which has a similar definition as the antenna gain, but this gain does not account for the antenna loss. Th e power gain and the directive gain of the antenna are usually considered to be the same except that the antenna efficiency is very low. We use same G to express both of them [20] . the system design, we use horn antenna and antenna array, which present narrow beamwidth, to obtain high gain and good isolation. 3.1.2 on, usually referred to as RCS , is a far-field parameter, which is use g properties of a radar target. For a target, there is mono e transmitter and receiver are at the same locati e part of the energy as heat or to direct it toward directions other both methods, shaping and materials, are used together in order to op at X-band. In Radar Cross Section The radar cross secti d to characterize the sc atterin static or backscattering RCS when th on and a bistatic RCS when the transmitter and receiver are not at the same location [21] . The RCS of a target can be controlled us ing primarily two basic methods: shaping and the use of materials. Shaping is used to attempt to direct the scattered energy toward directions other than the desire d. Materials are used to trap the incident energy within the target and to dissipat than the desired. Usually timize the performance of a radar target. Representativ e values of some typical targets are shown in Table 3-1 [21] . Note that these numbers are representative If the cross section of an adult male body is one, then the chest-wall area, which provides the heartbeat and respiration inform ation, should have a much smaller cross

PAGE 50

37 section. Because the calculation is quite complicated, in the design, the RCS is approximately estimated to be 0.01, same as that of a bird. This value is adopted to estimate the received power for the latter syst ems at all frequency band. It will give a receivObjects RCS (m ) ed signal power of 20 dB lower than that using the RCS of 1, but it is enough to meet the system sensitivity requirement. More details will be illustrated in Chapter 4. Table 3-1. RCS of so me typical targets. 2 Pickup Truck 200 Automobile 100 Cabi Large Fighter Aircraft 0.01 0.00001 n Cruiser Boat 10 6 Adult Male 1 Conventional Winged Missile 0.5 Bird Insect 3.1.3 f the receiver. Channel Noise Assuming the transmitted signal power is constant, then the received signal is corrupted by additive white Gaussian noise (AWGN) have a power spectral density equal to N 0 /2. The AWGN assumption proves adequate in taking into account the inherent noise o 3.2 RF Section Different from the communication systems, radar system does not need to modulate a baseband signal to its passband in the RF transmitter in Figure 3-1 . The transmitted wave is usually a pure carrier signal. When this signal is reflected back from a target, the time-varying signal about the chest-wall moveme nt is modulated as its excess phase and occupying a very narrow bandwidth. The demodula tion in the radar rece iver to extract the chest-wall movement information is simila r to that in the communication system.

PAGE 51

38 Minimum noise, low distortion, and low inte rference are indicators to assess the quality of the receiver. 3.2.1 RF Receiver As discussed in Chapter 2, indirect-conve rsion architecture with double-sideband transmission shows the advantage of reducing the DC offset and null point problem o ver ng di scussion about RF receiver is focusing on this indirect-conversion architecture. The block diagram is referred to Figure 2-6 . 3.2.1.1 Receiver bandwidth gh not carrying any baseband ormation around the passband, the two single-tone sideband signals are separated by two , thus require a system to have a wo fIF. ation for a 27 GHz carri er frequency. Also, components working at 27 GHz with 1 GHz bandwidth are easy to be obtained. However, as the carrier frequ can be obtained in terms of the noise figure (NF) and gain of each stage, and calculated by Friis equation: the single-tone transmission. The followi Althou inf f IF bandwidth of at least t Therefore, the IF frequency should be chosen according to the bandwidth availability of RF building blocks at differe nt carrier frequencies. In Chapter 2, an IF frequency from 450-MHz to 800-MHz was show n with a good tuning range and enough global null point separ ency decreases, broad bandwidth becomes difficult to achieve, especially for circuits on silicon. Therefore, to balance the tuning range, the null point separation, and the bandwidth, the IF frequency was chosen to be around 200 MHz when a 5GHz system was integrated on a chip. 3.2.1.2 Receiver noise figure For a cascade of stages in the receiver path in Figure 2-6 , the overall noise figure

PAGE 52

39 ... 1 1 )1(13 2NF NF NF NF 21 1 1 pp p totAAA (3.2) where A p 1 , A p 2 repre sent the gain of the first and the second stages. The noise contributed by ea m can o-noi se ratio (SNR), and written as tput SNR. Because the bandwidth of the wanted signals is ver PA is very important to achieve longer working time for the . Furthermore, the radiati on power should meet the IEEE safety mW/cm2 for frequency higher than 10 GHz. ch stage decreases as the gain preceding the stage increases, implying that the first few stages in a cascade are the most critical. 3.2.1.3 Receiver sensitivity The receiver sensitivity is defined as th e minimum signal level that the syste detect with acceptable signal-t P sen = dBm/Hz + NF tot + 10log B + SNR min (3.3) where NF tot is the system total noise figure calculated by (3.2), B is the system bandwidth, and SNR min is system required ou y narrow, around 2 Hz, so the receiver ma y appear very sensitive. For instance, if NF tot = 6 dB and SNR = 20 dB, the receiver se nsitivity can achieve -145 dBm. Inserting this value to (3.1), the maximum detection distance may achieve more than 30 meters. 3.2.2 Transmitter Power As shown in Figure 2-6 , the transmitted signals are simply the mixing products of two LO sources and no power amplifier (PA) is applied. Because this system is for long term vital sign monitoring in short distance, so the transmitting power should be kept as low as possible. Moreover, because PA is th e most power consumi ng blocks in the RF transceiver, so eliminating battery powered portable syst em standard. Shown in Figure 3-2 is the IEEE RF safety guideline [22] . The maximum power density at 5 GHz in uncontrolled envi ronments should be lower than 5 mW/cm 2 , and lower than 10

PAGE 53

40 Figure 32. IEEE RF sa fety guideline [22]. 3.2 Baseband Section The baseband section is mainly working for amplifying and filtering. It was first designed including preamplifier (PreAMP), band pass filter (BPF), and baseband amplifier (BB_AMP) using LM324 low power operational amplifiers (op-amp). Shown in Figure 3-3 is the block diagram of the baseband section. Figure 3-3. Baseband section incl udes PreAMP, BPF, and BB_AMP. The PreAMP and BB_AMP adopt the same topology, which is shown in Figure 3-4 . The voltage gain is decided by R1/R3. The resistors R1 or R3 can be replaced by a potentiometer to achieve a variable gain control. BPF PreAMP BB_AMP

PAGE 54

41 Vin Vout R1 100 kR3 1 k Figure 3-4. Schematic of the PreAMP and BB_AMP. The band pass filter (BPF) is composed of an active high pass filter (HPF) and an ctive low pass filter (LPF), has an approxi mate pass band of 0.2-Hz to 10-Hz. The schematics of HPF and LPF are shown in thdboard, worked with the Kaband system, and helped realize the vital si gn detection successfully. However, since the filtering of low frequency (0.2~10 Hz) signal requires huge resistors as show in Figure 35, additional thermal noise was introduced to the noisy baseband signal, thus degraded e baseband SNR. redesigned to only contain a B uch as autocorrelation. This filtering in software can be easily implemented and is reconfigurable. a Figure 3-5 (b) and (c), respectively. They are realized by 5 order butterworth filter architectures using Sallen & Key circuit. Transfer function of BPF is shown in Figure 3-6 with the bandwidth of 0.2 Hz. The whole baseband circuitry was implemen ted on a brea th Therefore, in the latter meas urement, the baseband circui try was B_AMP to provide certain amplif ication and remove PreAMP and BPF. The baseband filtering was implemented in signa l processing section in the LabVIEW program, which also performs other functions s

PAGE 55

42 (a) HPF LPF Vin Vout 100mF 150F 150F 150F 150F 5.1 k1000 pF 10 k10 k 5.1 k10 k5.1 k10 k1000 k (b) Vin Vout 0.19F 0.13F 0.16F 80 k 0.51F 0.049F 80 k80 k80 k80 k (c) Figure 3-5. Schematic of the band pass fil ter . (a) Band pass filter is composed of HPF and LPF; (b) Schematic of HPF; (c) Schematic of LPF. Figure 3-6. Transfer function of BPF with bandwidth of 0.2 Hz. 3.3 Signal Processing Section The amplified baseband signa l is digitized by a 22-bi t USB data acquisition module (IOtech Personal DAQ/54) before sending to the laptop for signal processing. The

PAGE 56

43 sampling rate is 37.037 Hz. A LabVIEW program is developed to process the data in real time and to save the data for post-processing. The saved data will be further analyzed by a MATLAB program to calculate the detect ion accuracy. The LabVIEW block diagram for real time signal analysis is show in Figure 3-7 . Figure 3-7. LabVIEW block diagram for real time signal analysis. The heartbeat and breath signals are first separated by a 4th order Butterworth bandpass filter with pass band from 0.1-Hz to 0.6 -Hz (for breathing rate of 6-36 breaths per minute) and a 4th order Butterworth band-pa ss filter with pass band from 0.7-Hz to 2-Hz (for heartbeat rate of 42-120 beats per minut e). The frequency ranges should be able to cover the scenarios of normal persons. For people with bradycardia, the filter frequency range can be adjusted. process the signal. All calculations are performe this i After filtering, a sliding window is added to the data str eam to d on the data inside the window . A window size is 13.824-s: nterval provided enough data for reliabl e calculation but coul d still track rapid Filtering Sliding Window Hanning Window Center Clipping Auto Correlation “Undo” Window FFT Reference Heartbeat B(t) Heartbeat Breathing Respiration Rate Heartbeat Rate Comparison Reference Heartbeat Rate Heart-Rate curacy Ac

PAGE 57

44 changes in heart or respirati on rate. The sliding window is shifted over the waveform in one-sample increments. In each window, the received signal is processed by hanning window, center clipping, auto-correlation and tone measurem ent algorithm to iden tify the signals of interest. The received baseband signal as well as the calculated respiration and heartbeat rates was displayed in real time and saved in data files during measurement. Hanning window is used to prevent spec tral leakage and improved the an alysis of acquired signals. Center clipper, which is commonly used in the processing of audio data, is used to remove unwanted peaks in the signal. A commonly used method to determine the pe riod of a signal is the autocorrelation function. One of the properties of the autocorrelation function is that if the input signal contains a periodic component , the autocorrelation functi on will contain a periodic [23] . The resulting output signal after autocorrelation further analyzed by a similar MATLAB program procedure is applied to the reference hear tbeat signal to obtain the dynamical reference c omponent with the same frequency and compress the random noise contains peaks at integer inte rvals of the period of the signal. FFT was then applied to the autocorr elated signals to obtain the respiration and heartbeat rates. During the measurement, a wired finge rtip pulse sensor (UFI_1010 pulse transducer) was attached to the subject’s finger to provide the reference heartbeat rate [16] [17] . The saved data for post processing is to calculate the detection accuracy. The detected heartbeat signal was finally evaluated by “heart-rate accuracy”. Since the heartbeat rate of a person may be dynami cally changing, the same signal processing

PAGE 58

45 heartbeat rate as well. Heart-rate accuracy is calculated as the percentage of time the detected rate is within 2% of the reference rate. We call this % as a confidence interval. When tbeat signal can only obtained by complicated calcu e interested signals, the receiver could be very sensitive even with poor receiv the detected heartbeat rate falls into this confidence interval, then this rate is considered accurate. Because there was no refe rence available for a breathing signal, its detection accuracy wi ll not be calculated [23] [24] . A screen capture of the real time signal analysis is given in Figure 3-8 . The detected signal in time doma in, which is displayed in th e upper left window, shows the rough respiration signal. The h eartbeat signal is modulated on that. Respiration signal is always obvious, but the weak hear lations. That is also the reason why we only focus on the heart-rate accuracy computation. 3.4 Summary In this chapter, the system architecture was discussed from design point of view. According to the radar range equation, RF section discussion was focused on the receiver NF and sensitivity discussion for a certain SNR. It was shown that due to the very narrow bandwidth of th er NF tot . Meanwhile, the other two important parts: baseband section and signal processing section were discussed as well.

PAGE 59

46 Figur e 3-8. A screen capture of the real time signal analysis.

PAGE 60

CHAPTER 4 KA-BAND VITAL SIGN MONITORING SYSTEM A Ka-band system that can detect human heartbeat and respiration signals with double sideband transmission will be demonstrated in this chapter. This Ka-band radar sensor offers several advantages over pr eviously reported systems operating at low microwave frequencies [4] –[9]. First, the low microwav e bands are crowded and occupied by many other applications. For example, the 2.4-GHz ISM band is used for wireless LAN, cordless phones, Bluetooth, etc. In c ontrast, the Ka-band spectrum is still sparsely used and has less interference. S econd, the shorter wavelength is more sensitiv to small displacement. According to (1.3), th e modulated phase in the baseband output is e displacement, the shorter wavelength will generate a larger phase modul ation. Finally, due to short wavelength at Ka-band, the antenna can be made very small a nd can be possibly integr ated with the rest of the circuits on a semiconductor chip [25] . 4.1 System Description The block diagram of the Ka-band vital sign monitoring system is shown in Figure 4-1 . The receiver in the RF section includ es a low noise amplifier (LNA), two downconverters (Rx_Mixer1 and Rx_Mixer2), and an IF amplifier (IF_AMP ). The transmitter in the RF section contains an up-conve rter (Tx_Mixer). A receiving antenna (Rx_Antenna) and a transmitting antenna (Tx_Antenna) are for receiving and transmitting signals. Baseband section is composed of a preamplifier (PreAMP), a band pass filter (BPF), and a low frequency amplifier (LF_AMP) [16] –[18] . inversely proportional to the wavelength. For the same 47

PAGE 61

48 Figure 4-1. Block diagram of the Ka -band vital sign monitoring system. 4.1.1 RF Section receiver, which were built with commercial parts as individual blocks, which were connected by 50 SMA cables. Their specifications and manufacturers are listed in Table 4-1 . Two local oscillators (LO’s) generate signals S1( t ) (with frequency f1) and S2( t ) (with frequency f2). Two 3-dB power splitters are used to divide the power of S1( t ) and S2( t ), with half of the power sent to the transmitter chain and the other half sent to the receiver chain. As shown in Figure 4-1 , the RF section of the Ka -band vital sign monitoring system is composed of a transmitter and a Signal Processing (f2-f1, f2, f2+f1) R (t ) 2 Reference Heartbeat Rx_Antenna B ( t ) Transmitter LNA LO2 S 2 (t ) (f 2 ) Power Splitter 1 Rx_Mixer1 IF_AMP BPF Tx_Mixer R ( t ) R 1 (t) PreAMP LO1 S 1 (t ) (f 1 ) DAQ Module (f2-f1, f2, f2+f1) T t ( ) Tx_Antenna Rx_Mixer2 Receiver Baseband LF_AMP Power Splitter 2

PAGE 62

49 Table 4-1. Ka-band system RF section bu ilding blocks and their specifications. Blocks Manufacturer Specifications LO1 Mini-Circuit 450-800MHz; Power: 11dBm LO2 Avantek 20-40GHz; Power: 10dBm Tx_Mixer Rx_Mixer1 Miteq RF/LO: 4-40GHz; IF: 0.5-20GHz; Conversion Loss: 10dB Rx_Mixer2 Mini-Circuit RF/LO: 0.3-4.3GHz; IF: 0.01-2.4GHz; Conversion Loss: 6.42dB Power Splitter1 Narda 10-40GHz; 3dB Power Splitter2 Narda 0.5-18GHz; 3dB LNA Miteq 26-40GHz; Gain: 27dB; NF: 3dB IF_AMP Miteq 0.1-8GHz; Gain: 33dB; P1dB: 13dB Since there is no filter following the Tx_Mixer, the output T ( t ) of the Tx_Mixer has two main frequency components: lower sideband fL = f2 f1 and upper sideband fU = f2 + f1. Normally, there is one more frequency component f2 in the output of Tx_Mixer, which is the leakage from LO2. The output power spectrum of the transmitter measured at antenna connector is shown in Figure 4-2 . 26 26.5 27 27.5 28 28.5 -110 -10 -100 -90 -80 -70 -6 0 -5 0 -40 -30 -20 RBW: 3MHz 26.54 GHz VBW: 3MHz -21.1 dBm 27.10 GHz -18.3 dBm ) er (dBm Pow Frequency (GHz) 27.66 GHz -23.3 dBm The resolution bandwidth and the video bandwidth were both set at 3MHz. The lower sideband and upper sideband frequencies are 26.54-GHz and 27.66-GHz with power levels of -21.1-dBm and -23.3dBm, respectively. The 27.10-GHz signal in between is the LO2 leakage due to non-id eal port-to-port isol ation of Tx_Mixer. Figure 4-2. The output spectrum of the transm itter, measured at the antenna connector.

PAGE 63

50 Although the LO leakage is evid ent, it does not affect th e baseband signal d etection, which will be discuss eceiver n indirect-conve cn the re the receive om the s onito is correlated to signal T ( t ) but with phase m by the tiying chest-wall nversion, signa ation, downconverted from the f2 component in the received signal R ( t ). If a direct down-conversion architecture is employed, the DC offset may introduce severe problems such as saturating the baseband circuits. The large DC offset and the near DC signals are removed by the bandpass frequency response of the IF_AMP before second do wn conversion to baseband. Therefore, in the following discussions, the f2 component in the transmitted wave will be ignored because it does not affect the baseband signal. After the second down conversion, the output R2( t ) consists of baseband signals carrying the subject’s chest-wall motion in formation and other unwanted high frequency 4.1.2 Antennas r ed later on. The r uses a rsi on architecture that employs two-step d signal R ( t ) is the reflected wave fr onversion. I ceiver chain, ubject being m red. It the transmitted odulated me-var position. After the first down co l R 1 ( t ) consists of two modulated signals at f 1 , down-converted from lower sideband f L = f 2 f 1 and upper sideband f U = f 2 + f 1 , respectively. The chestwall motion information is modulated on the phases of these two signals at f 1 . In addition, it also has a DC offset due to the self-mixing of LO2 leakage transmission, and a baseband signal car rying chest-wall motion inform spurs, which will be filtered out by the baseband circuits. Two types of low-profile printed patch an tennas were designed and fabricated for use in the measurement. One is a printed single-patch antenna fabricated on a high frequency substrate material, GML1000, with dielectric constant of 3.2 and substrate

PAGE 64

51 thickness of 0.762-mm. The si ze is about 5 x 5 mm 2 . The photography is shown in Figure 4-3 (a). This antenna achieves a maximum antenna gain of 3.9 dB at 31 GHz and an estim .9-dB at 28-GHz and an estimated beam ity gain, therefore increases the e and reduces interference from other radio devices at other directions. The c ated beamwidth of 60 x 80. It achieves a gain of 0.5 dB around the operating frequency 27 GHz. The antenna characteristic of gain and S 11 are shown in Figure 4-4 (a). Because no chamber was available, the ante nna gain was estimate d by the Friis equation with the measured data in free space. (a) (b) Figure 4-3. Photography of two types of ante nnas. (a). Single-patch antenna; (b). 4x4 antenna array. The other antenna is a 4 x 4 printed patch antenna array fabricated on the Rogers RO3003 PTFE/Ceramic laminates with r of 3.0 and substrate thickness of 0.508-mm. The total size is 20.9 x 28.2 mm 2 . The photography is shown in Figure 4-3 (b). This antenna array achieves a maximum antenna ga in of 12 width of 10 x 10. The antenn a characteristic is shown in Figure 4-4 (b). Same types of antennas were used in transmitting and receiving. Compared to the single-patch antenna, the antenna array has higher directiv detection distanc omparison of detection accuracy between these two antennas will be shown later. Also, horn antennas were used in some experiments for better directivity.

PAGE 65

52 -50 -40 -30 -10 0 10Inut Rectn Cefficit (d)-40 -30 -10 0 10RatadBi) -20 2628303234363840 Frequency (GHz) (a)peflio oenB-50 -20diaion Gin ( -30 -25In C-15dBi) -20 -15 -10 -5 0 5put Reflection oefficient (dB)-20 -10 -5 0 5 10 15Radiation Gain ( 4x4 antenna array. ter 3. The schem 2628303234363840 Frequency (GHz) (b)Figure 4-4. Radiation gain and S 11 of two types of antennas. (a) Single-patch antenna; (b). 4.1.3 Baseband Circuitry The baseband section is same as the firs t version discussed in Chap atic of each block can be referred to Figure 3-4 and Figure 3-5 . The signal R 2 ( t ) from the Rx_Mixer2 in Figure 4-1 was first sent to the preamplifier PreAMP to enlarge its amplitude by 20 dB, then the bandpass filte r BPF, which has a passband of 0.1-Hz to 10-Hz, filtered out the high frequency component s of the amplified signal and only left

PAGE 66

53 the wanted signals. Finally, the filtered si gnal was amplified furthermore through the low frequency amplifier LF_AMP by 40 dB to achieve the baseband signal B ( t ). 4.1.4 Signal Processing The signal processing part is the same as that discussed in Chapter 3. Because no respiration reference was available, onl y heart-rate accuracy was evaluated. 4.2 Ka-band Link Budget Because of short wavelength and no obstacl es between the system and the target, line-of-sight (LOS) free space propag ation is approximted. Shown in Figure 4-5 is the propagation channel of the monitoring system. Distance between the system and the subject is d. Using (3.1), the antenna received signal, whic h is reflected back at a distance of 3 m (indoor environment), for a single-patch an tenna is about -123 dBm, and -105 dBm for antenna array. The detailed data for each parameter is shown in Table 42 . a Figure 4-5. Propagation channel of the Ka-band monitoring system. Table 42. Received signal power for 27 GHz system Single-Patch Antenna Array Frequency 27 GHz 27 GHz P t -18.5 dBm -18.5 dBm Antenna Gain 0.5 dB 12.9 dB Cross Section 0.01 m20.01 m2Distance 3 m (indoor) 3 m (indoor) Prmin-130 dBm -105 dBm R espiration Heart d

PAGE 67

54 To guarantee the radar can detect the vita l sign at 3 m distance successfully with a high detection probability, the ra dar receiver must have suffici ently high se nsitivity. To e the system sens itivity and NF, the block diagram of the Kaband e cumulative gain is 44 dB. tem. To guarantee a high detection accuracy and probability, the output SNR is set to be as high as 20 dB. Therefore, the receiver se nsitivity for 2 Hz bandwidth is calculated in Table 4-3 . The link margin for the Ka-band syst em achieves at leas t 17.7 dB if using single-patch antenna. On the other word, this means this system is able to detect the target at farther distance if the required link margin is lower than 17.7 dB. However, during the measurement, when the distan ce was approaching longer than 3 m, the at signal was buried, ame very low if using the present signal processing method. ll these components’ specs, ante nnas’ specs, and base band circuitry’s specs, a simulation was run in ADS to show how the received signAnt G=-10dB be convenient to calculat transceiver is shown in Figure 4-6 with listed specificati ons of each building block. Using Friis equation, the overall NF of the receiver is about 3.1 dB and th Antenna enna Figure 4-6. Block diagram of the RF s ection of the Ka-band monitoring sysG=27dB NF=3dB G=33dB NF=1.3dB received signal was accompanied with lots of noise, the weak heartbe and thus the calculated heartbeat detection ac curacy bec Having a al varies with the B (t ) G=-10dB G=-6.4dB LNA Mixer IFamp Mixer Splitter Splitter LO1 LO2 IL = 3dB IL = 3dB

PAGE 68

55 distan Single-Patch Antenna Array ce. Without loss of generality, only the heartb eat signal was modeled. The block diagram is shown in Figure 4-7 . Table 4-3. Receiver sensitivity and link margin Received Power -130 dBm -105 dBm Thermal Noise -174 dBm/Hz -174 dBm/Hz -147.7 dBm -147.7 dBm 17.7 dB 42.7 dB SNR 20 dB 20 dB Rx NF 3.3 dB 3.3 dB Sensitivity Link Margin Shown in Figure 4-8 is the simulation results at 1 m and 3 m, respectively. As the detecting distance increases, the strength of the received signal decreases. Note that, the weak signal at 3 m is caused by the long-di stance propagation loss, and is completely different from the null point issue discussed in Chapter 2. Attenuator ATTEN1 VSWR=1 Loss=15 dB Antenna_XMIT XMIT_Antenna1 Frequency=Carrier_Frequency Gain=12.9 dB Bandwidth=1.5 GHz Source_CW CW1 Frequency=Carrier_Frequency Power=12 mW CW Source_CW_IF CW2 Po Fre IF wer=10 mW quency=IF_Frequency UpConvertor UpConvertor4 ConvGain=-10 dB IF Amplifier AMP3 RF LO S21=sqrt(Gain) PhaseShiftSML DownConvertor ConvGain=-6.4 dB DownConvertor2 RF IF LO Baseband_Circuits X2B a s e b a n d 2 1DownConvertor1 ConvGain=-10 dB DownConvertor RF IF LO Amplifier_LNA LNA2 NF=1.3 dB Gain=33 dB PwrSplit2 PWR2 S21=0.707 S31=0.707 PM_ModTuned MOD1 Sensitivity=10 Rout=50 Ohm Fnom=RF1 Term Term1 Z=50 MOhm Num=1 Test_Point_A TPA1 Amplifier_LNA LNA1 NF=3 dB Gain=27 dB Antenna_RCV Bandwidth=1.5 GHz RCV_Antenna1 Frequency=Carrier_Frequency Gain=12.9 dB PwrSplit2 PWR3 S21=0.707 S31=0.707 PS3 Phase=4*180*Range/Wavelength VtDataset SRC4 Expression="T3" Dataset="source.ds" Figure 4-7. Schematic of the Ka-band monitoring system.

PAGE 69

56 e Reference Heartbeat Amd plitu Reference Heartbeat e Amd (a) plitu Reference Heartbeat Am plitude Reference Heartbeat Am plitude (b) Figure 4-8. ADS simulation result s on heartbeat detection. (a) at a distance of 1 m; (b) at a distance of 3 m. 4.3 Measurement Results The Ka-band monitoring system was tested in the lab environment. A photograph of the measurement setup is shown in Figure 4-9 . A wired fingertip pulse sensor (UFI_1010 pulse transducer) was at tached to the index finger during the m easurement to provide the reference heartbeat signal. Measured at Short Distance ith LO frequencies f2 = 27.1GHz and f1 = 560-MHz. The subject, facing the an tenna, was seated approximately 0.5-m away and facing the antenna. The frequencies were determined experimentally by tuning the LO frequencies of the Ka-band radio, wh ich was the result of the antenna bandwidth 4.3.1 Heartbeat and Respiration The heartbeat and breathing signals were measured w

PAGE 70

57 in combination with transceiver gain freque ncy response. The total output power of the two sidebands from the transmitter, measured at antenna connector, was only 12.5W (7.8W for LSB and 4.7W for USB. LO leakage excluded since no contribution to baseband). Ka-Band Radio Laptop for Signal Processing DA Q Module Baseband C ircu its Antennas Finger-pressure Sensor for Reference Figure 4-9. Measurement setup for h eartbeat and respiration detection. The baseband signal detected by the remote monitoring system (solid line) and the reference h shed line) sampled within 20-s period are shown in Figure 4-10 (a). Their frequency spe g the FFT to the whole 20-s detec bea tings per minute (BPM), which matches the ect ed signal was further proce eartbeat signal (da ctrums obtaine d by applyin ted signals are shown in Figure 4-10 (b). The horizontal axis represents breathing and heartbeat rates per minute. As shown in the figure, the respirati on rate is about 21 breathings per minute (BPM). The heartbeat rate is about 75 reference heartbeat rate. To assess the detec tion accuracy, the det ssed by utilizing the signal processing procedure discussed in Chapter 3 to extract the periodic heartbeat and breathing signals and calculate heart-rate accuracy. After obtaining the respiration and heartbeat rate , two narrow windows were applied to the detected signal to filter out the respirati on and heartbeat signals separately, one has the

PAGE 71

58 center frequency of respirati on rate, and the other has the center frequency of heartbeat rate. The results are shown in Figure 4-11 . The heartbeat signal detected from a distance of 0.5 m away achieved an accuracy of 100% from the calculation, and the filtered-out heartbeat sig nal matched the reference heartbeat very well too [16] . 0 2 4 6 8 10 12 14 16 18 20 -1 -0.5 0 0.5 1 Time (S) (a)Amplitude (V) 0 20 40 60 80 100 120 0 100 200 300 Amplitude Respiration Heartbeat Rate (Times/Minute) ( b ) Figure 4-10. Detected (solid line) and reference (dashed line, not in the same scale) signals in (a) time domain and (b) frequency domain. 4.3.2 Heartbeat and Respiration Measured over Variable Distance With the same setup as in the previous 0.5-m-distance measurement, heart-rate accuracy at different distances with differe nt antennas was measured and compared. The result of heart-rate accuracy versus distance is shown in Table 4-4 . As the distance is increased, the amplitude of the detected signal becomes smaller and harder to be detected due to the incr eased signal loss when propagating over a longer distance, thus reducing heart-rate accurac y. The longest detection distance that can achieve better than 80% accuracy is 1.5-m for single patch antenna and 2.0-m for the antenna array. The antenna array achieved a higher accuracy and longer distance than

PAGE 72

59 single patch antenna as expected. Comp ared to previous reported data [4]– [9] in low frequency, this is a promising result because higher frequency electromagnetic waves usually suffer higher signal loss traveli ng in air than low frequency waves. 0 1 2 3 4 5 6 7 8 9 10 -1 0 1 Baseband B(t) (V) 0 1 2 3 4 5 6 7 8 9 10 -0.5 0 0.5 Detected Respiration 0 1 2 3 4 5 6 7 8 9 10 -3 0 3 x 10-4 Detected Heartbeat 0 1 2 3 4 5 6 7 8 9 10 -0.03 0 0.03 0.06 Time (S)Reference Heartbeat B ( t ) is shown at the top, follo wed by the signal processed ntenna and a 4x4 Dista Figure 4-11. Baseband signal respiration and heartbeat signals. The re ference heartbeat signal is shown at the bottom. The comparison of heartbeat signal with the reference shows a very good match. Table 4-4. Heart-Rate Accuracy Comparis on Between a Single Patch A Antenna Array over Different Distances from 0.5 Meters to 2.5 Meters. nce Between the Subject and the Radar (m) Single Patch Antenna HeartRate Accuracy (%) Antenna Array HeartRate Accuracy (%) 0.5 100 100 1 92.3 96 1.5 83.2 89. 3 2 65.7 81.5 2.5 43.4 64.6 above the ion 4.3.3 Heartbeat and Respiration Measurement with Obstacles The measurement setup shown in Figure 4-12 was the same as the experiments, except that a large 4’x4’ 2-cm-thick wood board was inserted between target and the sensor antenna. The purpose of th is experiment is to find the penetrat

PAGE 73

60 capability of the high frequency electromagnetic wave and the robustness of this sys The measurement results illustrate that a h eart-rate accuracy of 81.8% was achieved a 1-m distance. tem. t a Figure 4-12. Measurement setup having a 4’x4’ 2-cm-thick w ood board inserting between the monitoring system and the subject. its dielectr in wood for a 2.45-GHz wave is from 3cm to 350-cm depending on the dielectric constant an n this m nknown, the Doppler radar is relatively robust for wood (r=2.0~2.6). More investigations on different m ferent dielectri tants are being carried out (BPF) in the baseband circuits. The BPF was substituted with a low pass filter (LPF) that Microwave penetration depth is proportional to its wavele ngth and square root of ic constant, but i nversely proportional to its loss factor. The penetration depth d loss factor [26] . Although the loss factor of th e wood board used i easurement is u measurement re sults demonstrate that this Ka-band aterials with dif c cons . 4.3.4 Single-Tone Sound Measurement To explore more applications for the Ka-b and monitoring system, an experiment of detecting acoustic signal was designed. In this measurement, the system was the same as those used to detect the heartbeat and respiration signals except for the band pass filter

PAGE 74

61 had cut-off frequency at 1-KHz. The reco rded time-domain signa l and its frequency spectrum are shown in Figure 4-13 . When a single-tone 100-Hz sound signal was sent to a speaker, the speaker was humming, and its surface was vibrati ng at the same frequency accordingly . Similar to the heartbeat and respiration detection, the Doppl er radar can detect the small displacement due to the speaker surface vibration as well. The 100-Hz tone was detected clearly, while the much weaker second and third harmonics were also detected. More experiments on acoustic signal detection will be carried out in the future work. One potential application for this is remote sensing of human speech pattern by detecting the surface vibration of throat [27] . 100Hz Figure 4-13. Result of Doppler radar sensor used for sound detection. (a) time-domain, (b) frequency-domain.

PAGE 75

62 4.3.5 Null Point Elimination with Frequency Sweeping As discussed in Chapter 2, the detection accuracy depends on the subject’s position that m ight be in the null point, the optimum point, or somewhere in between. However, the optimal point can always be achieved by tuning the f 1 frequency, thereby high detection accuracy can always be achieved no matter where the subject is. An experiment was set up at a distance of about 1-m, and the measur ement results are shown in Figure 414 (a) and (b), respectively. Figure 4-14. Heartbeat detection at null point and optimum point. Th e heart-rate accuracy is 54.5% at the null point (a) while 94% at the optimum point (b). The frequency difference between them is only 56-MHz.

PAGE 76

63 Theoretically, a null point can be switc hed to an o ptimum point when tuning f1 frequ point by tuning f1 by an odd multiple of 18.75-MHz. 4.3.6 Measurement under the Different Power Levels and from Different Body Sides The heartbeat and respiration signals were measured with LO frequencies f2 = 27.1GHz and f1 = 560-MHz, which is the same as the above setup. The experiment conditions were designed as combinations of the following parameters : two power levels of 350-W and 14.2-W; five different distances from the antenna: 0.5-m, 1-m, 1.5-m, 2-m, and 2.5-m; and measuring from four sides of the body as shown in Figure 4-15 . ency by an odd multiple of 18.75-MH z. One null point was determined experimentally, at f 1 = 616-MHz, where a low detection accuracy of 54.5% was observed. Based on the theory, a frequency step f = 3 x 18.75 = 56.25-MHz was subtracted from 616-MHz to give f 1 = 559.75-MHz. The measurement made at f 1 = 560-MHz shows that a high accuracy of 94% was achieved. This experi ment verified the theory that a null point can be changed to an optimum Front Back Left-Side Right-Side Front Back Left-Side Right-Side Figure 4-15. Topview of the test setup. listed in T tennas were replaced by The measured results of heart-rate accura cy for all the above combinations are able 4-5 . In this measurement, the original patch an

PAGE 77

64 comm 14.2W ercial horn antennas with gain around 20dB each. As expected, we achieved better heart-rate accuracy at longer distance by us ing high-gain and high-directivity antennas. Table 4-5. Summary of Hear t-Rate Detection Accuracy Distance (m) Front Left Right Back 0.5 99.1% 96.3% 100% 97.6% 1 89.8% 89.8% 93.2% 100% 1.5 98.9% 89% 93.8% 94.3% 2 85.2% 80.5% 97.4% 93.6% 2.5 83.3% 85.7% 85.1% 85.5% 350W 0.5 100% 100% 100% 100% 1 94.8% 94.7% 93.2% 100% 1.5 98.1% 97.6% 100% 100% 2 2.5 100% 100% 100% 100% 95.1% 100% 95.2% 97.2% ible to detect the vital signs no matter what the body’s orient ations are? The answer is positive. From Table 4-5 , the detection accuracy from any side of the body is better than 80%. In addition, the measurement from the back shows the best performance, which will be discussed later on. The results also indicate that better accu racy can be achieved with higher power, as expected. Figure 4-16 shows a 25-s data measur ed from the body’s front side at 2-m distance using 350-W power. The wired fingertip pulse sensor provides a standard reference for heartbeat. Since e heartbeat rate of a person may be dynami cally changing, the same signal processing eartbeat signal as well. In Figure 4-16 (b), the black The previously reported monitoring syst ems only showed the detection ability when the subject facing the antenna [4] – [9] [11] [16] [17] . However, in practical applications, the patients might turn ar ound when monitoring sleep apnea, the human victims buried under earthquake rubble might no t exactly face up. Is it poss th procedure is applied to the reference h solid curve shows the detected heartbeat rate in beats per minute (BPM), the grey

PAGE 78

65 solid curve shows the referenced heartbeat rate in BPM. Two grey dotted lines show the upper and lower limit of the acceptable heartbeat rate, which is 2% variation from th e ence interval. When the detected fto this confid inte rval, then this rate is consid [18] . referenced heartbeat rate. This region is cal led the confid heartbeat rate alls in ence ered accurate 0 5 10 15 20 25 -3 -2 -1 0 1 2 3 De tec ted Si gn al ( V) Time (Sec) (a) 0 5 10 15 20 25 80 95 85 90 Time (Sec) (b)BeatsMin / Detected Heart Beat Reference Heart Beat 2% Higer than Reference 2% Lower than Reference Figure 4-16. Detected signal at 2-m distance, in time domain (a) and heart-rate comparison (b) measured from the front of the human body with the power level of 350-W. 4.4 Harmonic Interference at Ka-band From the above measurement results in Table 4-5 , it can be seen th at the heart-rate accuracy detected from the back is better than from other sides. By analyzing the spectra, we discovered an apparent di fference between the spectra m easured from the front and from the back. Figure 417 shows the normalized spectra of the signals detected from the front and the back of the body at 1.5-m distance and under th e power level of 350-W. It

PAGE 79

66 shows stronger harmonics of the respiration signal when detecting from the front than from the back. 0 20 40 60 80 100 120 0 0.2 0.4 0.6 0.8 1 Beats/Min (a)Normalized SpecBreathing Breathing 2nd Harmonic Breathing 3rd Harmonic Heartbeat trumFundamental 0 20 40 60 80 100 120 0 0.2 0.4 0.6 0.8 1 Beats/Min (b)Normalized SpectrumBreathing Fundamental Breathing 2nd Harmonic Breathing 3rd Harmonic Heartbeat Figure 417. Normalized spectrum comparison at 1.5-m distance, from the front (a) and the back (b) under power lever of 350-W. From the front, the amplitude of heartbeat is on the order of 0.01-mm, but that of shows the simulated spectrum of B ( t ) under typical values of h eartbeat and respiration. It agrees with the measured sp respiration increases in frequency and amplitude, the third order harmonic grows larger and moves closer to the location of the heartbeat in the spectrum, resulting in a destructive interference to h eartbeat signal. respiration is on the order of 1-mm as observed, which is much larger. Figure 418 ectrum to a cer tain extent. As the subject’s

PAGE 80

67 On the other hand, the amplitude of respiration from the back is found to be comparable to that of heartb eat. In this case, the problem of harmonics is significantly reduced. Figure 418 (b) shows the simulated spectrum when measured from the back. 0 20 40 60 80 100 120 0 0.2 0.4 0.6 0.8 1 Beats/Min (a)Normalized SpectrumBreathing Fundamental Breathing 2nd Harmonic Breathing 3rd HarmonicHeartbeat 1 0 20 40 60 80 100 120 0.8 0.6 0.4 0.2 0 Beats/Min (b) Normalized SpectrumBreathing Fundamental Heartbeat Breathing 2nd Harmonic Figur sideband transm ission was successfully demonstrated for the first time. The short wavelength at Ka-ban d increases the sensitivity of phase shift e 418. Simulated normalized spectrum comparison, for the front case (a) and the back case (b). In addition to the nonlinearity due to tr ansfer function, the nonlinearity due to electronic circuits may also contribute to the harmonics. However, the latter was minimized by increasing the system dynamic range during measurement [18] . 4.5 Summary A Ka-band monitoring system that can detect human heartbeat and breathing signals using low-power double

PAGE 81

68 due to a null point to an optimum point, resulting in almost doubling the detection accuracy. Also, indirect-conversion receiver ar chitecture reduces the DC offset and 1/f noise that can degrade signal-to-noise rati o and detection accuracy. Excep t heartbeat and respiration detection, acoustic signal has also been succes sfully detected by the Ka-band system. In addition, this Ka-band system demonstrated the robustness in detecting the vital sign through a thick wood board. Different from the previously reported syst ems, this Ka-band system has also been demonstrated the ability to detect heartbeat and respiration signa l from a human body’s four different sides and show n sufficiently high detection acc uracy of over 80% at 2.5-m distance. The result of the best detection accuracy when measuring from the body’s back was analyzed and explained by a nonlinear model. small displacement and therefore impr oves the signal-to-noise ratio and detection distance. The use of double sideband transmi ssion helps resolve the null point problem and improves the detection reliability. Freque ncy tuning technique is applied to switch

PAGE 82

CHAPTER 5 5 GHZ PORTABLE VITAL SI GN MONITORING MODULES Ka-band non-contact vital sign monitoring sy stem has been discussed in Chapter 4. It has been shown that the short wavelength at Ka-band benefited the heartbeat detection and the double-sideband transmission method resolved the severe null point problem occurring at short-wavelength detection. The double-sideband transmission simplified the system hardware for potent ial monolithic integration since no image-reject filter is neede ts but depends on the amplitude of respiration [29] . For people having a large chest-wa ll movement when breathing, lower frequency system is better. 5 GHz components are popular and cheap in the market and easy to obtain. Also, the wavelength at 5 GHz is much longer than that of Ka-band, thus reduce the harmonics of respiration and their interference on the heartbeat detection to a certain extent. However, longer wavelength at 5 GHz will have a penalty on the sensitivity of the heartbeat detection. In this chapter, a low-power 5-GHz m onitoring system employing double-sideband transmission was designed and built on a palm-s ize PCB and integrated in a system with PCB antennas and a data acquisition (DAQ) module, all powered from a laptop d, while keeping heterodyne architecture's benefit of low DC offset. However, it was shown that the harm onics of respiration signal and the intermodulation products of respiration and hear tbeat signals occurring at such detection using short wavelength may interfere the detect ion of heartbeat rate and thus reduce its accuracy. Therefore, an optimum frequency exis 69

PAGE 83

70 computer's USB port. For the purpose of comparison, a direct-c onversion nonquadrature module and a direct-conversion quadrature module were designed and built as well. 5.1 Portable Indirect-Conversion Module The b e-sideband transm Figure 5-1. Block diagram of a 5GHz vital sign monitoring system. ixer1 and Mixer2), and one IF_AMP. lock diagram of 5 GHz indirect-conversion system with doubl ission is shown in Figure 5-1 . Similar to the Ka-band system, it is composed of RF transceiver section, antennas, baseband s ection, and LabVIEW signa l processing section. 5.1.1 RF Transceiver Section The RF transceiver section constitutes with a transmitter, a receiver, and two LO sources. The transmitter includes only one mixer (Mixer3), and the receiver includes one LNA, two mixers (M The frequencies of LO1 and LO2 are 5.37 GHz and 300 MHz. Their power is divided by two, one half is fed to the transmitter, and the other half is fed to the receiver. Correlation Auto Filter Algorithm Tone Measurement Save to File B_AMP Baseband DC_Block RF Transceiver TxA RxA IF_AMP LNA Power Power O1 Splitter1 Splitter2 LO2 L LabVIEW Mixer3 Mixer2 Mixer1 Fingertip Sensor (Reference) DAQ

PAGE 84

71 In the transmitter, the Mixer3 is used to mix LO1 and LO2 signals to obtain two sidebands, one of which is at 4.93 GHz, and the other one is at 5.81 GHz. The comb ined transmitted power from and noise figure of the receiver are 21.2 dB and 1.52 dB, respectively. The components used in 5 GHz transceiver and their co rresponding specifications are listed in Table 5-1 . Table 5-1. Components used in 5 GHz module and their specifications. Blocks Manufacturer Specifications both sidebands is about 50 W. In the receiver, the LNA has gain of 18 dB and noise figure of 1.3 dB, whereas mixer1 and mixer2 are passive mixers w ith conversion loss of 7 dB and 6.8 dB, respectively. The IF_AMP has gain of 17 dB and noise figure of 5.5 dB. The overall gain LO2 Mini-Circuit 300-500MHz; Power: 6dBm Mixer3 Mixer1 M/A-COM RF/LO: 4.2-6.0GHz; IF: DC-2GHz; Conversion Loss: 6.8dB Mixer2 Mini-Circuit RF/LO: 0.02-1GHz; IF: DC-1GHz; Conversion Loss: 7dB Power Splitter1 Wilkinson Self Made; 3dB Power Splitter2 Mini-Circuit 1-650MHz; 3dB LNA Triquint 4.9-5.9GHz; Gain: 18dB; NF: 1.3dB IF_AMP Mini-Circuit DC-1GHz; Gain: 17dB; NF: 1.5dB Because a commercial packaged oscillator was not found when making this module, LO1 was designed using Agilent ATF36077 PH EMT, and fabricated on the Rogers O3203 PTFE/Ceramic laminates with r of 3.0 and substrate thickness of 0.508 mm The schematic of the oscillator is shown in Figure 5-2 . This oscillator includes three parts: resonator, oscillator core, and buffer. The resonator is a LC ne twork, which sets the oscillating frequency. The oscillator core is a two-port negative re sistance topology with the inductor L generating unstable condition. The buffer stage is a simple one-stage amplifier built by ATF36077 PHEMT. This buffer can provide certain isolation from the oscillator core to the output load. At the same time, the w hole oscillator output power is . R

PAGE 85

72 enhanced by the buffer to a certain extent too. The input, output, and the inter-stage matching networks are completed by 50 transmission lines. 16ATF 36077 L 50 ++ ATF 36077 Resonator Oscillator Core Buffer Figure 5-2. Schematic oscillator. ator d individua st. The circuit oscillated at 5and achiev er of 9.65 spectrum sho of a 5 GHz The oscill was fabrica te lly on board fi r .82 GHz ed output pow dB m. The measured output powe r is wn in Figure 5-3 . Phase noise achieves -114dBc/Hz at 1MHz. 5.6 5.65 5.7 5.75 5.8 5.85 5.9 5.95 6 -120 -100 -80 -60 -40 -20 0 20 9.65dBm at 5.82GHzdBm Freq (GHz) 5.6 5.65 5.7 5.75 5.8 5.85 5.9 5.95 6 -120 -100 -80 -60 -20 -40 0 20 9.65dBm at 5.82GHzdBm Freq (GHz) Figure 5-3. Output power spectr um of a discrete oscillator.

PAGE 86

73 The oscillator worked very well and the performance agreed with the simulation results when it was built alone. However, when the oscillato r was integrated with the other RF components on one board, due to the varying load and other interferences, the oscillator on the module board was oscillati ng at a lower value. The photography of the circuit board including all RF components is shown in Figure 5-4 . The board size is about 10 x 6 mm2. The output power spectrum of the transmitter output is shown in Figure 55 . The oscillator LO1 was oscillating at 5.37 GHz. Because of the nonlinearity of the RF components, harmonic spurs are shown in the spectrum too. Figure 5-4. Photography of the indirect-conversi on circuit board. 4.5 5 5.5 6 6.5 -140 -120 -100 -80 -60 -40 -20 0 Freq (GHz)dBm5.37 GHz -9.78 dBm 5.81 GHz -16.56 dBm 4.93 GHz -15.39 dBm 4.5 5 5.5 6 6.5 -140 -120 -100 -80 -60 -40 -20 0 Freq (GHz)dBm5.37 GHz -9.78 dBm 5.81 GHz -16.56 dBm 4.93 GHz -15.39 dBm Figure 55. Power spectrum of the transmitter output.

PAGE 87

74 5.1.2 Antennas Antenna TxA is used to transmit the signal and antenna RxA is used to receive the reflected signal. Antennas are low-profile 2x2 printed patch antenna arrays, which were fabricated on a high frequency substrate ma terial, GML1000, with dielectric constant r of 3.2 and substrate thickness of 0.762 mm. The antenna achie ved a maximum gain of 9.7 dB at 5.8 GHz and an estimated beam width of 20 x 20. The phot ography of the printed 2x2 patch antenna array and its measured S 11 is shown in Figure 5-6 , respectively. (a) (b) Figure 5-6. Photography and Measured S11 of printed 2x2 patch antenna array. 5 5.2 5.4 5.6 5.8 6 6.2 6.4 6.6 6.8 0 -5 -10 7 GHz -25 -20 -15 dB

PAGE 88

75 5.1.3 Baseband S ection VIEW program was developed to process the data in real time. A slid ing window of 13.824 seconds was added to the data stream to process the signal. The received signal was processed by filtering, auto-correlation, and t one measurement algorithm to identify the signals of interest. The received baseband signa l as well as the calculated respiration and heartbeat rates was displayed in real time a nd saved in data files during measurement. efore, the measured data can be further analyzed after the measurement is completed. During the measurement, a wired fingertip pulse sensor (UFI_1010 pulse transducer) was attached to the subject’s finger to provide the reference heartbeat rate. 5.1.5 Link Budget Using (3.1), the antenna received signal us ing the above antenna array at distance of 3 m is about -96 dBm. The detailed data for each parameter are shown in Table 5-2 . Table 5-2. Received signal power for 5 GHz monitoring system 2x2 Antenna Array The baseband section contains a DC bloc k (DC_Block) and an amplifier (B_AMP) with gain of 40 dB, whereas the filtering is done in digital domain using a LabVIEW program. The digital filtering reduces the noi se introduced by the analog baseband filter. 5.1.4 Signal Processing Section After amplifying, The baseband signal was digitized by the DAQ module before sending to the laptop for signal processing. The sampling rate is 37.037 Hz. A Lab Ther Frequency 5.37 GHz Pt-13 d Antenna Gain 7 dB (lower than that at 5.8 GHz) Distance 3 m (indoor) Prmin-96 dBm Bm Cross Section 0.01 m 2

PAGE 89

76 Similar to the Ka-b and system calculati on, using Friis equation, 5 GHz receiver sensit Antenna Array ivity and link margin is shown in Table 5-3. Table 5-3. Receiver sensitivity and link margin Received Power -96 dBm Thermal Noise -174 dBm/Hz 20 dB Rx NF 1.51 dB Sens Link Margin 54 dB SNR itivity -150 dBm Therefore, the link margin for the 5 GHz system is about 54 dB. Similar to the Kaband system, this system also shows the poten tial to detect a targ et faraway, although all measurement was carried out indoor in less than 3 m distance. 5.1.6 Measurement Results A photograph of the complete system setup is shown in Figure 5-7. The DAQ module shown in the picture is the 22-bit-resolution USB A/ D converter (IOtech Personal DAQ/54) with input dynamic range of 31 mV to 20 V. 5-7. Photograph of the system setup. LabVIEW Signal Processing Antennas Cable for Data to Laptop F igure Cable for Power Supply from Laptop to PCB DAQ Module RF circuit Board

PAGE 90

77 The RF circuit board includes all RF components in Figure 5-1 , and was fabricated on the Rogers RO3203 PTFE/Ceramic laminates w ith r of 3.0 and substrate thickness of RF parts is 50 . The baseband board w e other side of the RF circu odule and the DAQ require a supply voltage of 5 V. An otop USB port can supply 5 V an mA for the external devices. The tal current drawn by the PCB board is about 50 mA. Antennas are passive and have no power consumption. DAQ module consumes most of the current, wh ich is about 350 mA. Therefore, the whole system needs about 400 mA from the laptop, which is within the 500 mA limit. Therefore, no additional power supp ly or battery is needed for this portable system a, and breathed normally. Because the respiration is always th e easiest detectable signal, same as Kaband system, only the heartbeat accuracy is evaluated. The heart-rate accuracy at different distances is listed in Table 5-4 . A measurement example with 92.4% heart-rate accuracy at a distance of 1.5 m is shown in Figure 5-8 . The system achieved 81.35% heart-rate accuracy at a dist ance as far as 2.8 m, which is comparable to the Ka-band system. Table 5-4. Heart-rate accur acy vs. the detecting distance Distance (m) HEART-RATE ACCURACY (%) 0.508 mm. The transmission line connecting all as attached to th it board. Both the radar m module rdinary lap d up to 500 to . The 5-GHz non-contact radar module was te sted in the lab environment. The subject was seated motionless at a distance away, facing the antenn 0.5 98.82% 1 91.71% 1.5 92.40% 2.8 81.35% 2 85.78%

PAGE 91

78 0 5 10 15 20 25 -0.0 0. 06 6 -0.04 -0.02 0 0.02 0.04 Detected signal (V) Time (Sec) (a) 0 5 10 15 20 25 85 70 75 80 Detected heart beat Reference heart beat Beats/Min Time (Sec) (b) Figure 5-8. Detected signals tem, the harmonics occu py quite a portion of the total energy of the respiration the heartbeat signal, a wrong decision will be made in the baseband. Therefore, the two systems play a co mplementary role in optimizing the performance. 5 GHz sensor system is advant ageous for the detection of the large chestfor 5-GHz non-contact vital sign monitoring system, in time domain (a) and detected heart-rates (b). Normalized spectrums of the baseband signal are shown in Figure 5-9 (a) and (b). For comparison, the normalized spectrums of Ka-band system are added as (c) and (d). In this experiment, the chest-wall movement due to respiration of the to-be-detected people is about 2.5-3 mm. It is obvious that the fundamental compon ent of the respiration signal concentrates most of the energy in the 5 GHz monitoring system, which means its harmonics are weak and play less effect on the heartbeat detection. In contrast, in the Kaband sys signal. Once the third order harmonic is st ronger than

PAGE 92

79 wall movement, and 27-GHz system is superior for the detection of the small chest-wall movement. Therefore, a dual-band operati on might be an efficient and economic approach to detect a people fr om any angle. This system is also suitable for different people or for the same person unde r different physical conditions. 0 20 40 60 80 100 120 0 0.2 0.4 0.6 0.8 1 Beats/Min (b)Normalized Spectrum1 0 20 40 60 80 100 120 0 0.2 0.4 0.6 0.8 1 Beats/Min (a)Normalized Spectrum1st Resp. 2nd Resp. Heartbeat s t Resp. Heartbeat 2nd Resp. 0 20 40 60 80 100 120 0 0.2 0.4 0.6 0.8 1 0 20 40 60 80 100 120 0 0.2 1 Beats/Min (c)N ormalizum1st Resp. 3rd Resp. Heartbeat ed Spec2nd Resp. tr 0.4 0.6 0.8 Normalized Spectrum2nd Resp. 1stesp. 3rd Resp. Heartbeat R Beats/Min (d) from the front (a) and the back (b), a nd Ka-band system from the front (c) and Figure 5-9. Normalized spectrums of the ba seband signal, measured by 5-GHz system the back (d). 5.2 Direct-Conversion Non-quadrature Module Similar to the 5 GHz indirect -conversion system shown in Figure 5-1 , the directconversion non-quadrature system is composed of RF transceive r module, antennas, baseband section, and signal processing secti on. Except the RF transceiver module, the other three sections are the same. The block diagram of the RF transceiver module is shown in Figure 510 . The architecture employs di rect-conversion non-quadrature topology.

PAGE 93

80 Figure 510. Block diagram of a 5-GHz indirect-conversion non-quadrature module. The module is composed of a LO circuit, a power splitter, an LNA, and a mixer. The LO signal is divided by two, one half is directly sent to the transmitting antenna (Tx_Antenna), and other half is sent to the mixer in the receiver. The LO circuit is the me as that used in the previous indirect-conversion module. The transmitted power is 2dBm, and the oscillating frequency is at 5.74GHz, a little deviate from 5.82 GHz. In the receiver, the LNA has gain of 18 dB and noise figure of 1.3 dB, whereas mixer is a passive mixer with conversion loss of 7 dB. The overall gain and noise figure of the receiver are 11 dB and 1.51 dB, re spectively. The components used in 5 GHz transceiver and their corresponding specifications are listed in Table 55 . Blocks sa Table 55. Components used in 5 GHz direct-conversion no n-quadrature module. Manufacturer Specifications LNA Triquint 4.9-5.9GHz; Gain: 18dB; NF: 1.3dB Mixer Mini-Circuit RF/LO: 0.02-1GHz; IF: DC-1GHz; Power Splitter Conversion Loss: 7dB Wilkinson Self Made; 3dB The photography of the circuit board incl uding all RF compone nts is shown in Antennas, baseband circuit, and the signal processing section are the same as that Figure 5-11 . The board size is about 6.5 x 4.5 mm2. used in the indirect-conversion module. It will not be repeated here. LNA Mixer Tx_Antenna Rx_Antenna Splitter LO B (t ) R (t ) T (t )

PAGE 94

81 Figure 5-11. Photography of the direct -conversion non-quadrature circuit board. 5.2.1 Link Budget Using (3.1), the antenna received signal us ing the above antenna array at distance of 3 m is about dBm. The detailed data for each parameter are shown in Table 5-2 . Table 5-6. Received signal power for 5 GHz monitoring system 2x2 Antenna Array Frequency 5.74 GHz Pt2 dBm Ante Cross Section 0.01 m Prmin-80 dBm nna Gain 8.2 dB (lower than that at 5.8 GHz) 2Distance 3 m (indoor) Because the receiver NF is mainly decided by the first and second stages, so this module has nearly the same sens itivity as that of indirect-c onversion version. That is -150 derefore, the r this direct-converison system is as large as 70 dBm. However, the overall ystem is lo on system by about 10 dB. 5.2.2 re 5-7 . Similarly, the radar module, the ba consumes about 350 mA. Therefore, the whole system needs abou t 380 mA from the laptop, which is within Bm. Th link margin fo gain of this s wer than that of indirect-conversi Measurement Results The complete system setup is referred to Figu seband board, and the DAQ module are powered by laptop USB connection. The total current drawn by the PCB board is a bout 30 mA. DAQ module

PAGE 95

82 the 500 mA limit. Therefore, no additional powe r supply or battery is needed for this portable system too. The module was tested in the lab environm ent. The subject was seated motionlessly at a distance away and breathed normally. Shown in Figure 512 is the detected results measured from the front side of the body at a 1 m distance away. Except some apparent ved. variance due to the body movement, nearly 100 % heart-rate accuracy can be achie 0 5 10 15 20 25 0.15 30 -0.05 0 0.05 0. 1 Timeet signal ected D 0 5 10 15 20 25 30 50 60 70 80 Beat s/ Min Time Figure 512. Detected time domain signal and heart rate from the front side of the body. 0 5 10 15 20 25 30 -0.04 -0.02 0 0.02 Tim eedl Detect signa 72 70 0 68 5 10 15 20 25 30 74 Timeeats/M BinFigure 5-13. Detected time do main signal and heart rate from the back side of the body.

PAGE 96

83 Also, a measurement was also conducted from the back side of the body. The measurement results are shown in Figure 5-13 . Nearly 100% heart-rate accuracy is achie tconversion quadrature system is composed of RF transceiver module, antennas, baseband section, and signal processing s ection too. Except the RF tran sceiver section, the other three sections are the same. The block diagra m of the RF transceiver module with directconversion quadrature arch itecture is shown in Figure 5-14 . Figure 5-14. Block diagram of a 5-GHz direct-conversion quadrature module. The module is composed of a LO circuit, two power splitters, an LNA, and two mixers. The LO signal is divided by two, one half is directly sent to the transmitting antenna (Tx_Antenna), and the other half is divided by two again with 90o phase difference and then fed to two mi xers in the receiver. The LO circuit is the same as that used in the previous indirect-conversion m odule. The transmitted power is -3dBm, and the oscillating frequency is at 5.74GHz. ved. Also, as high as 98.42% detection accuracy is achieved at an optimum point around 2.8 m distance. 5.3 Direct-Conversion Quadrature Module Similar to the 5 GHz indirect-conversion system shown in Figure 5-1 , the direc Splitter LNA Mixe r Tx_Antenna 0 90 BI(t ) Mixe r Rx_Antenna LO Splitter B Q (t )

PAGE 97

84 The components used in this module are th e same as those in the direct-conversion non-quadrature module. In the receiver, the L NA has gain of 18 dB and noise figure of 1.3 dB, whereas mixer is a passive mixer with conversion loss of 7 dB. The overall gain and noise figure of the r eceiver ar e 11 dB and 1.51 dB, respectively. The photograph pone nts is shown in Figur y of the circuit board incl uding all RF com e 5-15 . The board size is about 8 x 4.5 mm 2 . Antennas, baseband circuit, and the signal processing section are the same as that used in the indirect-conversion nonquadrature module. The link margin for this system is the same too, about 70 dBm. Figure 5-15. Photography of the dire ct-conversion quadrature circuit board. The complete system setup is referred to Figure 5-7 . Similarly, both the radar top USB conne ain. As illustrated in the figure (b), the heart beat rate from both I and Q channels completely falls into the 2% confidence interval, thus, module, the baseband board, and the DAQ module are powered by lap ction. The total current drawn by the PCB board is about 30 mA, same as the direct-conversion non-qudrature version. Ther efore, the whole system needs about 380 mA from the laptop, which is within the 500 mA limit. The module was tested in the lab envir onment. The detected signals at 0.5-m distance are shown in Figure 5-16 . Because two baseband signals are in quadrature, I and Q signals in (a) have a delay in time dom

PAGE 98

85 the de tection accuracy in both I and Q channe ls is 100% at 0.5-m distance. At the same distance of 2.6-m, 97% detection accuracy was achieved for this I/Q module. The detection accuracy versus the detecting distance is shown in Table 5-7 . 0 5 10 15 20 25 -1 0 1 l Ded Signa etect(a) 0 5 10 15 20 25 75 80 85 Time (Sec) (b)Beat s/Min Heart rate I Heart rate Q Reference heart rate Detected I Detected Q Figure 5-16. Detected signals for I and Q channel. (a). in time domain, (b) detected heart-rates comparison. Table 5-7. Detection accuracy versus detecting distance Distance I channel Q channel N o. of testing 0.5 m 100 % 100 % 1 100 % 98.88 % 1 1 m 84.50 % 90.73 % 2 1.5m 86.26 % 90.26 % 1 48.08 % 90.42 % 1 100 % 97.12 % 2 100 % 96.01 % 1 2m 90.42 % 92.97 % 2 2.6 m 97.60 % 55.59 % 2 5.4 Comparison The choice of radio arch itecture is very important to the overall system performance. Three types of radio architectur es for non-contact vita l sign detection are demonstrated and compared at 5 GHz: direct-conversion non-quadrature, direct

PAGE 99

86 conversion quadrature , and double-sideband indirect-conversion . From the measurement result, direct-conversion non-quadr ature architecture showed severe DC offset and null point problem, while direct-conversion quadrat ure architecture was pro ven to be a good method to alleviate the null point problem but DC offset is still present. Double-sideband indirect-conversion architecture has been shown as a better and simpler approach to alleviate the DC offset and nu ll point problems simultaneously. 5.4.1 Direct-Conversion Non-quadrature Module Direct-conversion non-quadratur e architecture, which was adopted in the earliest vital sign detection systems [4]–[9], is the simplest architecture. However, as mentioned before, direct-conversion non-quadrature arch itecture not only has a severe DC offset oltage that could saturate the following baseband circuit, but also has an unavoidable null point p egrades the detection stability. s dominated by the even order nics of the wannals, making the d signal too weato be identified. ntime, as discussepter 2, there is optimum poinxisting /8 away the nearest nulhere the wan ls can easily a detimum point. However, for a 5.5 GHz transmitted signal point is enc ountered every 13.6 mm, w e to the optimum point that it is unavoidable to easurement. Therefore, other architectures have to be used to solve the problem. 5.4.2 Direct-Conversio Using quadrature architecture in the receiv er is one way to solve the null point problem. The received signal is split into two and mixed with tw o quadrature signals from the LO separately. The resulting two ba seband signals will be in quadrature too, v roblem, which severely d When a null point occurs, the baseband signal i harmo ted sig wante k Mea d in Cha always an t e from l point, w ted signa be identified. It is desirable if the detection can always be m at the op l, the nul hich is so clos be encountered during the m n Quadrature Sensor Module

PAGE 100

87 thus at least one of them will not have the null point problem. If the I and Q channels can be properly combined to reconstruct the wa nted signals, this method can be guaranteed with high detection quality under any situations. Figure 5-17 shows an example of the detected si gnal and spectrum of this module. The detector was placed at the position where the Q channel was at the null point and I channel was at the optimum point. At the null point of Q channe l, respiration component all heartbeat signal in the was maximum, leading to a noticeable sec ond harmonic and very sm spectrum. While at the optimum point of I channel, the heartbeat signal was maximum, leading to accurate and robust heartbeat detection. 0 5 10 15 20 25 -1 0 1 DetectiV ed sgnal () I Q Time (S) 0 20 40 60 80 100 120 0 0.5 1 Beats/Minmedt Noraliz Specrum I Q conversion quadrature detector. 5.4.3 Double-Sideband Indirect-Conversion Sensor Module Figure 5-17. An example of detected signa l and normalized spectrum of the directe is another effective way to allevi Double-sideband indirect-conversion architectur ate the null point problem. The combined transmitted power of both sidebands is 13 dBm. The detection accuracy was 81.35% at the distance of 2.8m, which is slightly lower than the other two architectures. The main reason is the much lower transmitted

PAGE 101

88 power resulting in lower signal noise rati o. Nevertheless, the double-sideband indirect conversion shows an advantag e of robust detection without null-point problem. 5.4.4 Comparisons All three-sensor modules showed excellent detection capability at optimum points. Because of the LO leakage between the LO por t and the RF port of the mixer, DC offset is easily produced by self-mixi ng of LO signal in the mixer [32] . The higher the operating frequency, the poorer isolation the mixer tends to have. 5 GH z mixer used for both directconversion modules and the fi rst stage of indirect-convers ion module has typical 26 dB RF-LO isolation, while the 300 MHz mixer us ed for the second stage of indirectconversion module has typical 63 dB RF-LO is olation. For indirect-conversion, the DC offset is determined by the last stage. Appa rently, the DC offset of indirect-conversion module is much lower than th at of direct-conversion modules. Since high DC offset will overwhelm the wanted signals and thus de sensitize the effective detection, indirectconversion architecture is a better solution. Table 5-8 shows measurement results made at some typical positions including optimum points and null points. The re sult of direct-conversion non-quadrature architecture clearly shows null points and op timum points as expected. Unavoidable null oint is the disadvantage of the direct-conversion non-quadrature architecture. Quad lleviate the null point problem in directssing paths and it is hard to dis p rature architecture is a good way to a conversion architecture, but it needs two base band signal-proce tinguish which data gives more accurate result when the reference is absent. How to combine the I and Q channels together properl y is still a challenge awaiting solution. Double-sideband indirect-conversion architect ure combines the detection outputs of both sidebands automatically through downconversion. It does not require quadrature

PAGE 102

89 generation or quadrature VCO but a simple single-output VC O. Furthermore, frequencytuning technique can be used to achieve the global optimum point. Therefore, indirectre has much more stab ility than the othe r two architectures. TableDirect-conversion non-quadrature demodulation conversion architectu 5-8. Detection accur acy summary of three modules * 2.1m 23.3% (NP a ) 2.8m 98.42% (OP ) bDirect-conversion quadrature demodulation I-Channel Q-Channel 1m 84.50% (MP c ) 90.73% (MP) 1.5m 48.08% (NP) 90.42% (OP) 2.6m 97.60% (OP) 55.59% (NP) Double-sideband transmission 2.8m 81.35% a Null point. b Optimum point. c A position between the null poi nt and the optimum point. The distances listed in the table for NP , OP, and MP are approximate values. 5.5 Summary A portable non-contact vital sign monito ring system using 5 GHz radar was implemented for field test. The system ach *ieved good accuracy with low transmission powe tions. ectconve r. The low power radar module and the da ta acquisition module were both powered by the laptop through USB connection which also carries the data. This portable system can be conveniently used for non-contact detection of respiration and heartbeat of either a human or an animal subject, in various biol ogical, medical, and s ecurity applica By comparing three different architectur es used for the 5 GHz non-contact vital sign sensor modules, double-side band indirect-conversion architecture showed prominent advantages over the other two direct-conve rsion architectures. Direct-conversion nonquadrature architecture showed severe DC o ffset and null point problem, while dir rsion quadrature architectur e still had DC offset issue and difficulty in combing two channels after solving the nu ll point problem. All the above problems can be resolved by

PAGE 103

90 using the double-sideband indirect-conversion architecture. Without the need to use image reject filter, double-side band indirect-conversion archite cture is also suitable for monolithic integration.

PAGE 104

CHAPTER 6 5 GHZ VITAL SIGN SENSOR CHIP DESIGN Based on the discrete Ka-band monitoring system and 5 GHz portable module on a board, a 5 GHz vital sign monitoring system wa s finally integrated on a silicon chip in a 0.18-m foundry CMOS process. The chip adop ts indirect-conversion architecture with double sideband transmission to alleviate th e DC offset and null point problem. The block diagram is shown in Figure 6-1 . Different from Figure 2-6 , two power splitters were removed and LO signals were fed to the receiver and transmitter directly. Figure 6-1. Block diagram of 5 GHz vital-si gn monitoring system in tegrated on silicon chip. In the Ka-band system and 5 GHz modules , each building block is matched to 50 , so connections between blocks are via 50 SMA cables (Ka-band system) or via 50 transmission lines (5 GHz modules). A cascade system like this is easy to build and do not need to worry about the interface matching and signal reflection, but will lose a certain gain because of low 50 load. This loss is more critical for on-chip circuit because even one dB gain improvement becomes more and more difficult when the LNA Mixer1 IFamp Mixer2 Mixe r 3 LO1 LO2 B(t) T(t) R ( t ) 91

PAGE 105

92 process scales down continuous ly. For 5 GHz double-side tran smission system, without using external components like filters, all blocks can be directly connected via capacitive coupling. The input impedance of the next s the load of the current stage. Therefore, the drivin carefully, especially for tw 6.1.1 Low Noise Amplifier A low noise amplifier (LNA) is a critical circuit in a receiver chain. With adequate gain for the LNA, the total receiver noise fi gure is mainly set by the noise figure of the LNA and blocks preceding the LNA. Because of this, the amplifier has to be low noise at its name indicates. A differential LNA is commonly employed in the CMOS transceiver design to r consumption compared to a single-ended LNA, requires an off-chip balun with finite loss to convert the single ended signal from an an tenna to balanced/differential signal. This increases the component count and noise fi gure of the receiver. Also, antennas are external and single-ended devices, so for this project, single-ended LNA is chosen. The 5-GHz LNA employs a commonly used cascade common-source topology. Its simplified schematic and simulation results are illustrated in Figure 6-2 . tage will act as g capability of every bl ock should be concerned o LO circuits, which will have to drive two blocks simultaneously. If using the same antennas, baseband circ uitry, and signal pr ocessing program as those used in the 5 GHz portable modules, then the link margin for this receiver is not a problem. Therefore, the specification requirement like NF, IP3, and gain for each receiver block is not as rigorous as th e digital communication systems. 6.1 RF Blocks reduce the second order distortion. This, in addition to doubling the LNA powe

PAGE 106

93 Figure 6-2. Schematic of a 5-GHz L NA and its sim mance. the bondwire inductance, which tunes the LNA tal-to-metal capacitor, and C2 is the capacitor looki ng into the input of the fo following circuit is am e architecture, which provides a certain gain to compress the noise from the following ulated perfor L g is an off-chip inductor along with input to the desired band, L s provides the real part to the input impedance for matching. M 1 is a common-source transistor, and M 2 is a common-gate transistor. LNA output matching uses an on-chip inductor L d and a capacitive transformer which includes C 1 and C 2 . C 1 is me llowed stage. The simulation results are given in Figure 6-2 . This LNA achieved 17 dB gain and 1.6 dB NF. 6.1.2 Active Mixers As Friis equation indicates, the noise c ontributed by each stage decreases as the gain preceding the stage increases, implying that the first few stages in a cascade are the most critical. Conversely, if a stage exhibits a ttenuation, then the noise figure of the plified when referred to the input of that stage. Therefore, in the receiver path, the first mixer (Mixer1) right after the LNA is chosen to be an activ V dd 1.8V Current 5.4mA Power Consumption 9.7mW Gain 17dB NF 1.6dB IIP3 -11dBm In L Vg2 d Out C C bypass2 C bypass1 1 C 2 M 2 L s L g M 1

PAGE 107

94 stages. Except for gain, active mixer can provid e the better isolation between ports of the mixer [32] . If a mixer accommodates a differential LO signngle-e signal, it is called “single-balanced”. If a mixer operates w ith both differential LO and RF inputs, it is called “double-balanced”. The active version assume of a Gid is shown in Figure 6-3. M5 and M6 form a differential pair. The gate of M6 is ac grounded when it works for Mixer1. For Mixer3 in the transmitter pa th, because the RF and LO signal are fully ifferential, Mixer3 is connected as double-balanced. Ls is an on-chip inductor to 14tching transistors driven by differential L the double-balanced counterpart, the circuit is more rtheless, since the RF signal processed by the LNA is single ended, one of the input termin als of the double-balanced mixer (Mixer 1) is connected to a bias voltage. However, this in turn creates diffe rent propagation times for the two signal phases amplified by M5 and M6 in Figure 6-3 , leading to finite evenorder distortion, but this falls out of the wanted bandwidth. al but a si nde d RF s the form lbert cell an d improve mixer common mode rejection. Transistors M –M are swi O signals. The output of Mixer1 is IF frequency of 200 MHz, and loaded by the IFamp input impedance. For Mixer3, in order to drive 50 measurement equipmen t, its output signal goes to an off-chip matching network to match to 50 . The schematic and simulation results are shown in Figure 6-3 . This mixer achieved 12 dB gain. Although the single-bal anced configuration exhibits less input-referred noise for a given power dissipation than susceptible to noise in the LO signal. Neve

PAGE 108

95 Figure 6-3. Schematic of an active double-bala nced mixer and its simulated performance. 6.1.3 IF Amplifier The IF amplifier (IFamp) was designed as a differential amplifier with a sourcedegeneration resistor to improve the linearity. M and M are differential pairs. Because the operating frequency is low, in order to save chip space, the output used active load instead of the inductance load. M and M act as the active loads, which not only provide large gain, but also provide more headroom. The amplifier gain is approximately decided by 2R /R . The schematic is shown in Figure 6-4 . R and R are also working for common-mode feedback to set the bi as voltage of the transistors M and M . The simulation results are shown in Figure 6-4 too. The achieved maximum gain is 21 dB. The IIP3 is also improved to -1 dBm. 6.1.4 Passive Mixer Passive mixer has two advantages over its active counterparts. First, it achieves a higher IP3 if M1 to M4 experience a large gate-source overd rive voltage in the “on” state so that RF signal does not vary their on-resistance significantly. Second, it draws no 1 2 3 4 1 2 1 2 3 4 V dd 1.8V Current 4.8mA Consumption Power 8.6mW Gain 12dB IIP3 -10dBm LO+ LOLdLd LO+ IF+ IFM 2 M 3 M 4 M 1 M 5 RFM 6 RF+ L s

PAGE 109

96 power from the supply voltage. Because the cumulative gain of the preceding stages is more than 50dB, so the signal arriving at the RF input of Mixer2 is already large. To reduce the distortion, passive mixer with higher IP3 is chosen for Mixer 2. Meanwhile, it can save some power consumption for low power applications. ulated performance. atic is shown in Figure 6-5 . The passive mixer consists of four Vdd1.8V Figure 6-4. Schematic of an IF amplif ier and its simulated performance. Figure 6-5. Schematic of a passive mi xer and its sim R1R1R2Vin+ The passive mixer schem switches (M 1 to M 4 ) in a bridge configuration. Th e switches are driven by LO signals in antiphase, so that only one dia gonal pair of transistor s is conducting at any given time. When M 1 and M 4 are on, BBout equals RF, and when M 2 and M 3 are Current 2.0mA Power Consumption 3.6mW Gain 21dB IIP3 -1dBm Gain -6.3dB IIP3 8dBm LO+ LOLOBBout+ LO+ BBoutRF+ RFM M M 1 2 3 M 4 V b ias Vou + Vou t t M1M2M3M4 6 7VinM M

PAGE 110

97 conducting, BBout equals –RF. The achieved conve rsion gain is -6.3 dB, and IIP is about 8 dBm. The passive mixer nonetheless suffers from a number of severe drawbacks. First, because the gain of the circuit is less than unity, the noise o f the stage following the gnified when referred to RF signal. For sinusoidal LO signals, the gain is are simultaneously on for a cons i part of the period. Second, the large width required of M1 and M2 n-resistance leads to substantial capacitive feedthrough from LO to IF [32] . 6.1.5 Oscillators There are two LO sources in the transceiv1 is a RForking at 5-GHz band, and LO2 is an IF source working at 200MHz. LC-tank oscillator has shown good phase noise performance with low power employs a cross-coupled NMOS differentia l pair with LC tanks. The simplified schematic is shown in Figure 6-6 ; it includes on-chip inductors and on-chip varactors. M1 and M2 form the oscillator core; M3 and M4 operate as buffer stages, not only play a role to provide a constant load to the oscillator core and stabilioscillation frequency, but also contribute a certain gain. The oscillation freque ncy is decided by the L1 or L2 inductance, the varactor capacitance, and their parasitics; and the tuning range is und 5 GHz, and the tu mixer is ma even lower because M1 to M4 derable for low o er, LO source w consumption, thus it is a popular topology in high frequency design. 5-GHz oscillator thus ze the decided by the varactor tuning range too. The oscillator is oscillating aro ning range achieved is from 4.58 GHz to 5.72 GHz. On-chip spiral inductors occupy a lot of ch ip area, which is undesirable for cost and yield considerations. Also, for most CMOS processes, it is diffi cult to obtain a high quality factor (Q) inductor if not using some extra processing steps. Therefore, compared

PAGE 111

98 to LC oscillator, ring oscill ator can be easily integrated on-chip without any extra processin g steps. Moreover, ring oscillators normally occupy less chip area, which lowers the co 6.1.6 st. With an even number of delay cells, ring oscillators generate both in-phase and quadrature-phase outputs. However, because of their low Q, the phase noise performance is in general much poorer [33] . The block diagram and cell schematic are shown in Figure 6-7 . Figure 6-6. Simplified schematic of a 5 GHz VCO. The delay cell consists of one NMOS input pair (M 1 or M 2 ), one PMOS positive feedback pair (M 3 or M 5 ) for maintaining oscillation, one diode-connected PMOS pair (M 4 or M 6 ) for frequency tuning. The ring oscillat or consists of two delay cells for power-consumption and phase-noise minimizati on. After all, the oscillator is oscillating around 250 MHz, and the tuning range achieved is approximately from 180 MHz to 320 MHz. V bias M 5 L 3 L4 Performance of Integrated System The cascade blocks are capacitively coupled to each other, the simulated system performance is shown in Figure 6-8 for reference. There are no matching networks on M 1 M 2 M 3 M 4 Vout + L 1 L 2 V tune V out

PAGE 112

99 chip. The input matching network including L g between the receiving antenna and the input of LNA will be realized on board using surface mount components. The transmitter differential output will be converted to a si ngle-ended signal by an offchip transformer, and its matching network will be realized and tuned on board too. Figure 6-7. Schematic of a 200MHz ring oscillat or. (a). Block diagram. (b) Schematic of V one cell. These simulation results are achieved be fore the output ports matched to 50 . The power level of output signal RFout at two si debands is about 430mV each. The received baseband signal BBm (10 MHz signal as a te st baseband signal) is about 300mV. The chip was fabricated in a 0.18-m foundry CMOS process. The die photograph is shown in Figure 6-9 . The total size is 1.37 x 1.66 mm2. VoutM1 bias M2M3M4M5M6IN+ INOUTOUT+ M 7 IN+ OUT+ cell INOUTIN+ OUT+ cell INOUTVout+ ( a ) ( b )

PAGE 113

100 Figure 6-8. Simulated output spectrum. The upper two are transmitter outputs in time domain and frequency domain. The lo wer two are receiver baseband outputs in time domain and frequency domain. n monitoring system chip. Figure 6-9. Die photograph of the 5GHz vital-sig LO1 LO2 Mx3 Mx2 LNA Mx1 IFamp

PAGE 114

101 6.2 Summary An integrated vital-sign monitoring system on silicon working at 5 GHz is demonstrated. Each building blocks such as : LNA, mixers, IFamp, and LOs is discussed with typical topologies and simulated data . The simulated overall system performance was provided for reference.

PAGE 115

CHAPTER 7 7.1 Summary non-contact vital-sign monitoring sy stem using double-sideband transmission and frequency-tuning technique is proposed and demonstrated. According to the Doppler theory, a target with a time varying position, but a net zero velocity, will reflect the signal with its phase modulated proportionally to the timevarying target position. If the heartbeat and respiration signals are to be monitored, demodulating the phase will then give a signa l proportional to the chest-wall position that contains information about movement due to heartbeat and respiration, from which heart and respiration rates and signatures can be determined. Base d on this principle, a noncontact heart and respirati on monitor can be envisioned. Remote non-contact vital sign detec tion using microwave Doppler phase modulation effect has been studied for many years. Previously reported systems usually adopted single-sideband transmission and direct-conversion ar chitecture. This architecture is simple and eas y to be implemented, but a lot of problems occurred in these systems too. To achieve accurate, stable, and reliable detection, researchers have spent great efforts for more than two decades to solve several technical challenges. Among these challenges, the influence of clutter noise and phase noise can be alleviated by the range-correlation effect by applying the same transmitted signal to the receiver as the reference signal. Another tw o challenges, the harmonics of respiration signal and the intermodulati on products of respiration a nd heartbeat signals, which SUMMARY AND FUTURE WORK A 102

PAGE 116

103 increase with the operating frequency, may inte rfere with the detection of heartbeat rate and thus reduce its accuracy. For people ha ving a large chest-wall movement due to breathing, lower frequency system is better. The other two ch allenges, DC offset and null point, can be alleviated b itecture. It turns out that the low frequency double-sideband ith frequency tuning technique is a good sy stem was robust for some obsta n detecting heartb y choos ing the appropriate radio arch transmissi on w and simple solution to alleviate the a bove challenges together and simultaneously up to now. The whole work is devided by three stages. The first stage is a Ka-band monitoring system built with discrete RF building blocks. The Ka-b and Doppler radar described shows excellent results on detecting heartbea t and respiration signa ls. With a very low transmitted power of 14.2W, the detection accuracy is 100% at a distance of 0.5-m. The accuracy is still better than 80% even when the distance is as far as 2.0-m. Meanwhile, several conclusions were drawn. (1). Shorter wavelengt h showed the higher sensitivity on weak heartbeat detection. (2). Ka-band cles, like a 2-cm-thick wood board. (3). Ka-band system showed the capability of detecting acoustic signals. (4). Short wavelengt h at Ka-band gave strong harmonics of the respiration signal, which could desensitize th e heartbeat detection and thus degrade the detection accuracy. Based on the first stage Ka-band system, the second stage 5 GHz portable modules were built for field test and comparison. The module shows excellent results o eat and respiration signals t oo. With a low transmitted power of 20W, the detection accuracy achieves 81.35% at the distance of 2.8m. By comparison, 5 GHz modules achieved the following goals: (1). 5 GHz systems show ed apparent less

PAGE 117

104 harmonics of respiration than Ka-band system . (2). 5-GHz radar was built on a palm-size PCB and powered from a laptop computer's US B port, thus realized portable. (3). By comparing three modules with three different architectures (indire ct-conversion, directconversion nonquadrate, and direct-conve rsion quadrate), i ndirect-conversion architecture with double-sideba nd transmission was proved to be a simple and effective way to resolve all technique challenges and could easily be integrated without using the image reject filter. source inductor Ls. Based on the above two systems, the thir d stage is a 5 GHz monitoring system integrated on silicon. Each building blocks such as: LNA, mixers, IFamp, and LOs is discussed with typical topologies and simulated data. The simulated overall system performance was provided for reference. 7.2 Future Work 7.2.1 5 GHz Chip Testing The chip is tested on a two-layer FR4 board, the Chip-On-Board (COB) packaging techniques is used for circuit characteriz ation, and the bonding diagram is shown in Figure 7-1 . There are total 12 downbonds connected directly to ground under the chip to reduce the parasitic inductan ces between the on-chip gr ound and board ground. One of them is used for LNA The measured transmitter spectrum before matching is shown in Figure 7-2 . The 5.02 GHz signal shown in the middle is a LO leakeage and has the power of about -30 dBm, and the two sideband signals at 4.77 GHz and 5.27 GHz are about -38dBm each. The receiver part is still on testing. The whole input and output matching network tuning and the real time heartbeat and respiration measurement will be part of the future work.

PAGE 118

105 Figur e 7-1. Bonding diagram of the 5 GHz chip. Figure 7-2. Transmitter output spectrum. 7.2.2 Multi-Target Monitoring System As one important application, this monitoring system can be used for infant sleep apnea syndrome detection in the hospital ne wborn intensive care unit (NICU). Usually there are at least one infant in one room, so instead of installing sensors for every infant, a phased array antenna can realize monitoring multiple infants by less sensors. The operating sketch is shown in Figure 7-3 . -120.00 -100.00Frequency (Hz) -80.00Pow -60.00 0.00 4.60E+094.80E+095.00E+095.20E+095.40E+09er (d5.02GHz 5.27GHz -40.00 -20.00Bm)4.77GHz

PAGE 119

106 By sweeping the antenna beam with a certa in angle at a certain time interval, the vital sign information of infants in the same room can be monitored one by one. The realization of beam scanning could greatly lower the cost. Figure 7-3. Sketch of multiple targets monitoring system using phased array antenna. 7.2.3 Tunable Wideband or Multi-Band System As proposed in Chapter 2, a tunable wideband or multi-band system can be designed to detect the different respiration situation of th e same people or different people. An example of a two-band system using Ka-band and 5 GHz band is shown in Figure 7-4 . A two-band switch will receive the c ontrol signal from the baseband signal s mo re feasible, and switch its band accordingly. two ba nds needs to be considered carefully too. processing part who decides which band i However, how to choose the frequency of Another important issue is the frequency and phase stability of the oscillator. Although range-correlation effect reduces phase no ise, frequency drift is still a main issue for an ordinary VCO [34] . Therefore, a synthesizer might be necessary to replace the ordinary VCO for the long-term robust monitoring.

PAGE 120

107 Therefore, the future new system may be suggested to include the above three solutions to a single system to realize long-term multiple-su bject monitoring for diversified people. Figure 7-4. An example of a two-band system. Ka-band System 5GHz System Baseband Signal Processing

PAGE 121

APPENDIX RANGE CORRELATION EFFECTS It is well known that the performance of continuous wave and pulsed Doppler Radars in the presence of clutter is limite d by the phase and amplitude modulation noise sidebands of the local oscillator (LO) signal used to generate the transmitted signal and convert the received signal to some intermed iate frequency (IF). The net effect of the noise sidebands is to spread clutter energy in to the frequency region of the target signal least, reduce the target signal-to-clutter (SK) ratio. The above is illustrated in Figure A-1 . In Figure A-1 , fo is the carrier frequency and fd is the target Doppler frequency. It is assumed that the clutter is at zero Doppler [13]. Figure A-1. Transmitted and received signal spectra. (a) Ideal transmitted signal, (b) Received signal associated with ideal transmitted signal, (c) “Practical” transmitted signal that includes noise sidebands, (d) Received signal associated with “practical” transmitted signal [13]. and potentially obscure the target return or, at Clutte r fo fofo+ fd fo fofo+ fd(a) (b) (c) (d)Tar g e t Clutte r Tar g e t 108

PAGE 122

109 Figure A-1 (a) illustrates an ideal transmitted signal spectrum while Figure A-1 (b) is the spectrum of its associated target and cl utter return signal. The spectral spreading on the returned signal is that ca used by m scatters of the target and clutter. This spread is ca d clutter. Figure A-1 (c) illustr gure A-1 (d) is representative of the spectr um of the receiver input it might not be representative of the spectrum at the signal processor input. In order to form a proper representation of the spectrum at the signal processor input, it is necessary to incorporate an effect termed range correlation. Range correlation is a filtering effect that modifies the receiver input amplitude and phase noise spectra to form their counterparts at the input to the signal pro cessor. The word range in the term range correlation derives from the fact that the amount of correlation, and thus the amount of filtering, depends upon the range of the target or clutter cell b ing illuminated, i.e. the time delay between A fu normalized, transmitted signal, T(t), can be represented by [13] otion of the various lled natural spectrum of the target an ates the spectrum of a “practical” transmitted signal and Figure A-1 (d) is the spectrum of its associated target and clutter re turn signal. The spread and flat regions of the transmit signal are caused by the noise si debands. Since the rece ived spectrum is the convolution of the tran smit spectrum with the target and clutter natural spectrum, the received spectrum will also have more spread and flat regions when compared to those caused by the ideal transmitted signal. In Figure A-1 (d), the spread on the transmit signal and the target Doppler frequency are such that the target signal is almost obscured by the clutter signal. While Fi e the transmitted and received signals. nctional block diagram of the Radar configuration is shown in Figure A-2 . The

PAGE 123

110 )(2))(1()(tjtfjoetAtT (A.1) where A(t) is a random amplitude perturbation that is termed the amplitude noise, f o is the carrier frequency and (t) is a random phase perturbati on that is referred to as the phase noise. The amplitude and phase noise are what give rise to amplitude and phase noise sidebands on the transmitted signal, and cause the spectral spreading of the transmitted signal. The primary contributor to amplitude an d phase noise is the lo cal oscillator (LO). The transmitter elements (modulator, amplifiers , power tube, etc.) also add noise to the transmitted signal but their contributions are us ually negligible compared to that of the LO. Figure A-2. Functional ra dar block diagram [13]. It is assumed that (t) is a zero mean, stationary stochastic process with autocorrelation )()()( ttER (A.2) and the associated phase noi se spectrum is given by )]([)( RFfS (A.3) where F[.] denotes the Fourier transform, and the IF phase no ise spectrum is give by [20] cRf fSfS /2sin4)()(2 (A-4) Local Oscillator (LO) Transmitter Coherent Oscillator (CO HO) IF Signal Processor fo I Target T(t) f f F D Clutter f I F + f D R(t)

PAGE 124

111 where the term in brackets embodies the effect s ofange d relay, or range correlation, on the IF spectrum, and R is the range that the signal retu rned from a scatter (target or clutter). A(t) is assumed to be a zero mean, Stationa ry, Gaussian stochastic process with autocorrelation [13] )()()( tAtAERA (A.5) Its associated amplitude noise spectrum is given by [13] )]([)( A ARFfS (A.6) and t he IF amplitude noise spectrum is given by [13] (A.7) where the term in brackets embodies the effect s of range delay, or range correlation, on the amplitude noise contribution to the IF spectrum. It is assumed that A(t ) and (t) are independent. The range correlation filter effects are shown in Figure A-3. Range correlation rovides a high pass filt ering effect of the phase noise spectrum which tends to reduce the effects of phase noise at frequencies close ing effects on the amplitude noise spectrum. For low frequencies it causes a gain of 3dB and for higher frequencies it resu lts in unity ga A further illustration of the effects of range correlation is shown in Figure A-4 and Figure A-5 . Figure A-4 contains plots of the IF amplit ude and phase noise spectra when range correlation effects are omitted and Figure A-5 contains similar spectra when range A-4 are generic spectra. As can be seen from )()(2)/2cos4)(()(2ftRcRf fSfSdA A AA p to the IF. However, range correlation causes only minor filter in (0 dB). correlation effects are considered. The amp litude and phase noise spectra used in Figure Figure A-3 and Figure A-5, range

PAGE 125

112 correlation causes significant a ttenuation of the low freque ncy components of the phase noise spectrum. In contrast, range correlation has little e ffect on the amplitude noise spectrum, except for the addition of an osci llatory behavior at high frequencies [13]. Figur e A-3. Range correlation filter effects [13]. Figure A-4. IF amplitude and pha se noise spectra – without ra nge correlation effects [13].

PAGE 126

113 Figure A-5. IF amplitude and phase noise spectra – with ra nge correlation effects [13].

PAGE 127

REFERENCES [1] W. F. Feltz, H. B. Howell, R. O. Knutes on, H. M. Woolf, and H. E. Revercomb, “Near continuous profiling of temperature, moisture, and atmospheric stability using the Atmospheric Emitted Radiance Interferometer (AERI),” J. Appl. Meteor., vol. 42, pp. 584-597, 2003. [2] Stezer, C. G. Diskus, K. Lubke, and H. W. Thim, “Microwave position sensor with sub millimeter accuracy,” IEEE Trans. Microwave Theory Tech., vol. 47, pp. 26212624, Dec. 1999. [3] H. H. Meinel, “Commercial applications of millimeter waves history, present 9[4] . C. Lin, “Microwave sensing of phys iological movement and volume change: A review,” Bioelectromagnetics, vol. 13, pp. 557-565, 1992. [5] K. M. Chen, Y. Huang, J. Zhang, a nd A. Norman, “Microwave life-detection systems for searching human subjects under earthquake rubble and behind barrier,” IEEE Trans. Biomed. Eng., vol. 47, pp. 105-114, Jan. 2000. [6] D. Droitcour, V. M. Lubecke, J. Lin, O. Boric-Lubecke, “A microwave radio for Doppler radar sensing of vital signs,” IEEE MTT-S International Microwave Symposium Digest, pp. 175-178, May, 2001. [7] D. Droitcour, O. Boric-Lubecke, V. M. Lubecke, J. Lin, .25m CMOS and BiCMOS single chip direct conversion Doppl er radars for remote sensing of vital signs,” IEEE International Solid State Circuits Conference, Digest of Technical Papers, pp. 348-349, Feb. 2002. [8] D. Droitcour, O. Boric-Lubecke, V. M. Lubecke, J. Lin, and G. T. A. Kovac, “Range correlation and I/Q performance benefits in single-chip silicon Doppler radars for noncontact cardiopulmonary monitoring,” IEEE Trans. Microwave Theory and Techniques, vol. 52, pp. 838-848, March 2004. [9] J. C. Lin, “Noninvasive microwav e measurement of respiration”, Proceedings of IEEE Special Issue on Laboratory Automation , vol. 63, pp. 1530-1530, Oct. 1975. [10] J. Seals, S. R. Crowgey, and S. M. Sharpe, “Electromagnetic vital signs monitor,” Georgia Tech. Res. Inst., Atlanta, GA, Final Rep. Project A-3529-060, 1986. status, and future trends,” IEEE Trans. Microwave Theory Tech., vol. 43, pp. 163 1653, July 1995. J 114

PAGE 128

115 [11] Y. Immoreev, S. V. Samkov, “Ultra-wide band (UWB) radar for remote measuring of main parameters of patient’s vital activity,” IEEE International Workshop “The Ultra Wideband and Ultra Short Impulse Singals” (UWBUSIS'02), Kharkov, Ukraine, Oct. 2002. [12] R. S. Raven, "Requirements on mater oscillators for coherent radar," IEEE Proceedings, Vol. 54, No. 2, pp 237-243, February 1966. [14] tions for direct-conversion receivers,” IEEE Trans. Circuits and Systems-II: Analog and Digital Sig nal Processing, vol. 44, no. 6, pp. [15] urier transforms and their physical applications , Academic Press, 1973. [16] tem for remote de tection of cardiopulmonary motion,” Proc. 27th IEEE Annu. Engineering in Medicine and Biology Society Conf., September 1-4, [17] Y. Xiao, J. Lin, Olga Boric-Lubecke, and Victor M. Lubecke, “Frequency tuning 6-1579, June 12-16, 2006. [20] Merrill I. Skolnik, Introduction to Radar Systems, McGraw-Hill, 2001. [21] [22] IEEE RF Safety Guideline: http:// www.arrl.org/news/rfsafety/hbkrf.html. [23] digital signal processor for Doppler radar sensing of vital signs,” Proc. 23rd IEEE s [13] M. C. Budge, Jr. and M. P. Burt, "R ange correlation effects in radars", IEEE National Radar Conference, April 1993. Razavi, “Design considera 428-435, June 1997. C. Champeney, Fo Y. Xiao, J. Lin, O. Boric-Lubecke and V. M. Lubecke, “A Ka-band low power Doppler radar sys 2005. technique for remote detection of hear tbeat and respiration using low-power double-sideband transmi ssion in Ka-band”, IEEE Trans. Microwave Theory and Techniques, vol. 54, pp. 2023-2032, May, 2006. [18] Y. Xiao, C. Li, and J. Lin, “Accuracy of a low-power Ka-band non-contact heartbeat detector measured from four sides of a human body,” Proc. IEEE MTT-S International Microwave Symposium, pp. 157 [19] M. Singh and G. Ramachandran, “Reconstr uction of Sequential Cardiac In-Plane Displacement Patterns on the Chest Wall by Laser Speckle Interferometry,” IEEE Trans. Biomed. Eng., vol. 38, pp. 483-489, May 1991. Constantine A. Balanis, Antenna Theory Analysis and Design, John Wiley & Sons, Inc, 1997. Lohman, O. Boric-Lubecke, V. M. Lubeck e, P. W. Ong, and M. M. Sondhi, “A Annu. Engineering in Medicine and Biology Society Conf., vol. 4, pp. 3359-3362, 2001.

PAGE 129

116 [24] H. Yang and S Rhee, “Development of the ring sensor for healthcare automation,” Robot. Autonom. Syst., vol. 30, pp. 273-281, 2000. Lin and T. Itoh, “A [25] ctive integrated antennas,” IEEE Trans. Microwave Theory Tech., Vol. 42, No. 12, pp. 2186-2194, Dec. 1994. [26] ogy,” Industrial Heating, pp. 43-53, January 2005. [27] . J. Gable, “Denoising of human speech using combined acoustic and EM sensor signal processing,” Proc. IEEE, Acoustics, [28] Experiment and sp ectrum analysis of a low-power Ka-band heartbeat detector measuring from four sides of a human body,” To appear in IEEE [29] Li, J. Lin, “Optimal carrier frequency of non-contact vital sign de tectors”, to appear [30] radar,” Submitted to IEEE Senor Letters. [32] on, Inc. 1998. 38, August 31-September 3, ethod of , 2005. UF Invention Disclosure #11871. Ed Kubel, “Advancements in microwave heating technol C. Ng, G. C. Burnett, J. F. Holzrichter, T Speech, and Signal, vol. 1, pp. 229-232, 2000. Li, Y. Xiao, J. Lin, “ Trans. Microwave Theory and Techniques. in IEEE RWS. Y. Xiao, C. Li, J. Lin, “A portable non-contact vital sign mon itoring system using 5-GHz [31] Y. Xiao, J. Lin, “Comparison of radio architectures for a noncontact vital sign radar sensor operating at 5 GHz,” Submitted to IEE Electronic Letters. B. Razavi, RF Microelectronics, Pearson Educati [33] W. Tak, H. Luong, “A 900-MHz CMOS low-phase-noise voltage-controlled ring oscillator”, IEEE Trans. On Circuits and Systems–II: Aanlog and Digital Signal Processing, vol. 48, No. 2, pp. 216-221, Feb. 2001. [34] C. Li, J. Lin, Y. Xiao, “Robust Overni ght Monitoring of Human Vital Signs by a Non-contact Respiration a nd Heartbeat Detector,” 28th IEEE Annu. Engineering in Medicine and Biology Society Conference. pp. 2235-22 2006. [35] USPTO Provisional Patent Applicati on US60/727,529: System and m frequency tuning for remote detection us ing double-sided Ka-band signals, filed on October 17

PAGE 130

Yanming Xiao was born in Yangzhou, Jiangsu, China. She received a Bachelor of Scien Technology in China in 1994. She received a Ma ster of Science degree in electrical and comp Radio Frequency System On Ch ip (RFSOC) Research Group, at the University of Florida Depa ical and Computer Engineering. Her research interests include RF BIOGRAPHICAL SKETCH ce degree in electronic engineering from Nanjing University of Science and uter engineering from the University of Florida in 2002. In 2003, she joined the rtment of Electr non-contact vital sign monitoring system for biomedical applications, RF integrated circuit design, and RF system-on-chip design. 117