基于微多普勒特征的人体微动识别系统设计与实现
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摘要
目标运动对雷达回波信号存在多普勒调制,振动、转动和翻滚等微动形式激励的微多普勒特征为行进中的车辆、人员和动物等目标的探测与识别提供了新的技术途径。本文结合人体微动特性雷达测量系统开展基于人体微动特征的识别研究,介绍了雷达回波采集系统的整体方案规划、硬件研制、软件实现的全过程,并在此基础上开展了基于实测数据的人体微动识别研究。
本文首先引入了人微动的基本概念,阐述了论文的研究背景,分析了国内外关于人体微动特性的研究现状。
第二章首先介绍了微动特性雷达测量系统的结构和原理,结合雷达回波具有多成分和高幅值的特点,为滤除回波中的干扰信号和调整信号幅值以便进行实时采样,设计了信号预处理模块和数据采集模块；为保证数据传输的真实性、实时性和稳定性,选取了USB接口和以太网接口作为传输接口；最后分析了系统设计的合理性。
第三章介绍了雷达回波预处理过程中的电平增益控制、信号缓冲、信号滤波三级电路的设计；针对预处理模块输出信号特点,设计了数据采集和缓冲子模块；结合采集输出数据流特点,综合考虑便携性和开发成本等因素,完成了USB接口和以太网接口两路传输系统设计。
第四章首先建立了人体结构模型和运动模型,研究了人体躯干和四肢的微动特性,推导了人体微动的雷达回波解析式并进行了仿真实验。设计了人体行进时的雷达回波数据采集实验,对回波数据进行了分析,提取了行进周期和行进速率,并对单人或多人场景进行了分辨。
论文最后对课题工作进行了总结,指出了进一步的研究方向。第i页
The characteristics of micro-motion produced by the ground micro-motion target, such as Vehicles, human and animals, provide a new way for target detection and recognition. In this paper, based on the radar system for human micro-motion measurement, the micro-motion characteristics of walking human have been investigated. Firstly, the full design procedure of the radar sampling system consists of blue print design, hardware and software development. And based on the data produced by the radar system, the research for micro-motion features extraction has been investigated.
This paper firstly introduces the basic concepts of the human micro-motion and the research background, then the research state of human micro-motion in the domestic and abroad has been analyzed.
In chapter II, the author firstly introduces the structure and principle of the radar system, considering the target backscatter is a signals with multi-component and high-amplitude characteristics, the signal pre-processing module and data acquisition module has been designed in order to remove the interference signal and adjust the signal amplitude so that the real-time sampling will be much easier; taking the transmission for data without distortion, real-time and stability into considerations, the USB interface and Ethernet interface are selected as transmission interfaces. Finally analyse reasonality of systems design.
The third chapter describes three circuit design of the pre-process of the radar echo, such as the level gain controlling, the signal buffering and the signal filtering; for the characteristics of the output of the signal pre-processing module, the data collection and buffer sub-module has been designed; according to the features of the output data stream, and taking the system portable characteristic and development complexity into consideration, the design and implementation of two-way transmission system composing of USB interface and Ethernet interface has been accomplished.
In the fourth chapter, the mode of human body's structure and its movement is established, and the micro-motion characteristics of the trunk and limbs of human body have been studied, then we derived the formulas of the radar signal returned for walking human, and the corresponding experiments are carried out. The radar echoes of walking human have been collected and analyzed. Then the walking cycle and speed are estimated through those data. The resolving method for one or multiple targets is also interpreted in the end.
Summaries and future research are given at the end of this paper.
本文首先引入了人微动的基本概念,阐述了论文的研究背景,分析了国内外关于人体微动特性的研究现状。
第二章首先介绍了微动特性雷达测量系统的结构和原理,结合雷达回波具有多成分和高幅值的特点,为滤除回波中的干扰信号和调整信号幅值以便进行实时采样,设计了信号预处理模块和数据采集模块；为保证数据传输的真实性、实时性和稳定性,选取了USB接口和以太网接口作为传输接口；最后分析了系统设计的合理性。
第三章介绍了雷达回波预处理过程中的电平增益控制、信号缓冲、信号滤波三级电路的设计；针对预处理模块输出信号特点,设计了数据采集和缓冲子模块；结合采集输出数据流特点,综合考虑便携性和开发成本等因素,完成了USB接口和以太网接口两路传输系统设计。
第四章首先建立了人体结构模型和运动模型,研究了人体躯干和四肢的微动特性,推导了人体微动的雷达回波解析式并进行了仿真实验。设计了人体行进时的雷达回波数据采集实验,对回波数据进行了分析,提取了行进周期和行进速率,并对单人或多人场景进行了分辨。
论文最后对课题工作进行了总结,指出了进一步的研究方向。第i页
The characteristics of micro-motion produced by the ground micro-motion target, such as Vehicles, human and animals, provide a new way for target detection and recognition. In this paper, based on the radar system for human micro-motion measurement, the micro-motion characteristics of walking human have been investigated. Firstly, the full design procedure of the radar sampling system consists of blue print design, hardware and software development. And based on the data produced by the radar system, the research for micro-motion features extraction has been investigated.
This paper firstly introduces the basic concepts of the human micro-motion and the research background, then the research state of human micro-motion in the domestic and abroad has been analyzed.
In chapter II, the author firstly introduces the structure and principle of the radar system, considering the target backscatter is a signals with multi-component and high-amplitude characteristics, the signal pre-processing module and data acquisition module has been designed in order to remove the interference signal and adjust the signal amplitude so that the real-time sampling will be much easier; taking the transmission for data without distortion, real-time and stability into considerations, the USB interface and Ethernet interface are selected as transmission interfaces. Finally analyse reasonality of systems design.
The third chapter describes three circuit design of the pre-process of the radar echo, such as the level gain controlling, the signal buffering and the signal filtering; for the characteristics of the output of the signal pre-processing module, the data collection and buffer sub-module has been designed; according to the features of the output data stream, and taking the system portable characteristic and development complexity into consideration, the design and implementation of two-way transmission system composing of USB interface and Ethernet interface has been accomplished.
In the fourth chapter, the mode of human body's structure and its movement is established, and the micro-motion characteristics of the trunk and limbs of human body have been studied, then we derived the formulas of the radar signal returned for walking human, and the corresponding experiments are carried out. The radar echoes of walking human have been collected and analyzed. Then the walking cycle and speed are estimated through those data. The resolving method for one or multiple targets is also interpreted in the end.
Summaries and future research are given at the end of this paper.
引文
[1]丁鹭飞,耿富录.雷达原理[M].西安：西安电子科技大学出版社,2006.
[2]Chen V C. Micro-doppler effect of micro-motion dynamics:a review[C]. Proceedings of SPIE on Independent Component Analyses, Wavelets and Neural Networks,2003,150(4):240-249.
[3]Chen V C, Li F. Analysis of micro-Doppler signatures[J]. IEE Proceedings on Radar, Sonar and Navigation,2003,150(4):271-276.
[4]Gray J E, Addison S R. Effect of nonuniform target motion on radar backscattered waveforms[J]. IEE Proceedings on Radar, Sonar and Navigation,2003,150(4): 262-270.
[5]Setlur P, Amin M, Ahmad F, et al. Indoor imaging of targets enduring simple harmonic motion using Doppler radars[C]. Athens, Greece:Proceedings of the Fifth IEEE International Symposium on Signal Processing and Information Technology, 2005,37(1):141-146.
[6]Chen V C, Li F Y, Ho S S. Micro-Doppler Effect in Radar-Phenomenon, Model and Simulation Study[J]. IEEE Transactions on Aerospace and Electronic Systems, 2006,42(1):2-21.
[7]陈行勇.微动目标雷达特征提取技术研究[D].长沙：国防科技大学博士学位论文,2006.
[8]陈维锋,彭晋川,王云基,唐华,帅莉蓉.三种生命探测仪及其在地震救助中的应用[J],四川地震,2003,3：25-28.
[9]王健琪,王海滨,杨国胜,荆西京,杨波,董秀珍,邱立军.心冲击图的雷达式非接触检测技术研究[J].北京生物医学工程,2001,20(2)：112-113.
[10]Chuang HR, Devedra M, Wang H, Postow E. An X-band microwave life-detection systems[J]. IEEE Trans Biomed Eng,1986,33(7):697-701.
[11]路国华,王健琪,杨国胜,王海滨,荆西京,邱力军,杨波.一种人体生命体征检测的新方法[J].北京生物医学工程,2001,20(4)：275-278.
[12]严登俊,李伟,王贵琴.生物电磁学研究进展[J].电气电子教学学报,2007,29(3)：11-16.
[13]Thayaparan T, Abrol S, Riseborough E. Micro-Doppler radar signatures for intelligent target recognition[R]. technical memorandum DRDC Ottawa:TM, 2004,23(2):165-170.
[14]Chen V C. Spatial and Temporal Independent Component Analysis of Micro-Doppler Features[R]. U.S. Government work not protected by U.S. copyright.
[15]崔来友,白士红,张春林等.人体运动学模型的研究[J].机械设计与研究,2003,19(6)：10-13.
[16]郭巧.现在机器人学[M].北京：北京理工大学,1997.
[17]Boashash B.Time-Frequency Signal Analysis and Processing[M]. Amsterdam: ELSEVIER Ltd,2003,23:577-626.
[18]L·科恩,时-频分析：理论与应用[M].中国西安：西安交通大学出版社,1998.
[19]Boashash B, Sucic V. Resolution measure criteria for the objective assessment of the performance of quadratic time-frequency distributions[J]. IEEE Transactions on signal processing,2003,51(5):1253-1263.
[20]Lovell B. C, Williamson R. C and Boashash B. The relationship between instantaneous frequency and time-frequency representations[J]. IEEE Transactions on Signal Processing,1993,41(3):1458-1461.
[21]Ram S. S, Ling H. Simulation of Human MicroDopplers Using Computer Animation Data[C]. IEEE Conference on Radar,2008.
[22]Smith G E, Woodbridge K, Baker C J. Multistatic Micro-Doppler Signature Of Personnel[C]. IEEE Conference on Radar,2008.
[23]Lei J. J, Lu C. Target classification based on micro-Doppler signatures[C]. In: Proceedings of IEEE International Conference on Radar. Washington, USA, May 2005,23(4):179-183.
[24]Michael G, Anderson R L R. Micro-Doppler analysis of multiple frequency continuous wave radar signature[C]. Radar Sensor Technology XI:Proc. of SPIE, 2007.
[25]Aggelopoulos E, Karabetsos E, Uzunoglu N, et al. Microwave System for the Detection of Trapped Human Beings[J]. Proceedings of the IEEE International Symposium on Industrial Electronics,1995,1:187-192.
[26]Stove A. G, Sykes S. R. A Doppler-based automatic target classifier for a battlefield surveillance radar[J]. Proceedings of IEEE International Conference on Radar. Edinburgh, UK, October 2002,45:419-423.
[27]Otero M. Application of a continuous wave radar for human gait Recognition[R]. SPIE Proceedings of the Signal Processing, Sensor Fusion, and Target Recognition XIV,2005,5809:538-548.
[28]史林,姜敏,黄莉.基于谐波模型的生命探测雷达人体状态识别方法[J].西安电子科技大学学报(自然科学版),2005,32(2)：1 79-1 83.
[29]闫冯军,朱家兵.基于宽带调频的非接触式探人雷达信号检测[J].中国科技信息,2007,12：303-304.
[30]王健琪,王海滨,荆西京等.呼吸、心率的雷达式非接触检测系统设计与研究
[J].中国医疗器械杂志,2001,25(3)：132-135.
[3l]路国华,王健琪,杨国胜等.一种人体生命体征检测的新方法[J].北京生物医学工程,2001,20(4)：275-278.
[32]路国华,王健琪,杨国胜等.非接触生命体征检测系统中噪声的非线性压缩[J].中国医疗器械杂志,2001,25(6)：316-317.
[33]张翼.人体微动雷达特征研究[D].长沙国防科技大学博士学位论文,2008.
[34]严登俊,李伟,王贵琴等.生物电磁学研究进展[J].电气电子教学学报,2007,29(3)：11-16.
[35]薛园园.USB应用技术开发大全[M].北京：人民邮电出版社,2007.
[36]金炯泰,金奎焕.如何使用KEIL 8051 C编译器[M].北京：北京航空航天大学出版社,2002.
[37]胡晓军.开发WDM型USB设备客户驱动程序[J].中国数据通信,2002,2：51-53.
[38]孙鑫,余安萍.VC++深入详解[M].北京：电子工业出版社,2006.
[39]张颖,张长利,基于DSP的具有以太网接口的嵌入式系统设计[J],煤矿机械,2005.
[40]曲延滨,冯立国,苏健勇,DSPTMS320VC5402的以太网接口设计[J],微处理机,2004.
[4l]彭启琮,管庆.DSP集成开发环境：CCS及DSPBIOS的原理与应用[M].北京：电子工业出版社,2004.
[42]Boulic R, Magnenat-thalmann N, Thalmann D. A global human walking model with real-time kinematic personification[J]. The Visual Computer,1990,253(5): 344-358.
[43]Michael G. Anderson, Robert L. Rogers. Micro-Doppler analysis of multiple frequency continuous wave radar signatures, Radar Sensor Technology XI, edited by James L. Kurtz, Robert J. Tan, Proc. of SPIE Vol.6547,65470A, (2007).
[44]刘冰啸.虚拟环境下的人体运动建模与仿真方法研究[D].中国科学技术大学硕士学位论文,2005.
[45]绳涛.仿人机器人力信息反馈控制方法研究[D].长沙：国防科技大学硕士学位论文,2005.
[46]郭巧.现在机器人学[M].北京：北京理工大学,1997.
[47]Geisheimer J L, Greneker E, Marshall W S. A high-resolution Doppler model of human gait[C]. Proceedings of SPIE on Radar Technology,2002.365:8-18.
[2]Chen V C. Micro-doppler effect of micro-motion dynamics:a review[C]. Proceedings of SPIE on Independent Component Analyses, Wavelets and Neural Networks,2003,150(4):240-249.
[3]Chen V C, Li F. Analysis of micro-Doppler signatures[J]. IEE Proceedings on Radar, Sonar and Navigation,2003,150(4):271-276.
[4]Gray J E, Addison S R. Effect of nonuniform target motion on radar backscattered waveforms[J]. IEE Proceedings on Radar, Sonar and Navigation,2003,150(4): 262-270.
[5]Setlur P, Amin M, Ahmad F, et al. Indoor imaging of targets enduring simple harmonic motion using Doppler radars[C]. Athens, Greece:Proceedings of the Fifth IEEE International Symposium on Signal Processing and Information Technology, 2005,37(1):141-146.
[6]Chen V C, Li F Y, Ho S S. Micro-Doppler Effect in Radar-Phenomenon, Model and Simulation Study[J]. IEEE Transactions on Aerospace and Electronic Systems, 2006,42(1):2-21.
[7]陈行勇.微动目标雷达特征提取技术研究[D].长沙：国防科技大学博士学位论文,2006.
[8]陈维锋,彭晋川,王云基,唐华,帅莉蓉.三种生命探测仪及其在地震救助中的应用[J],四川地震,2003,3：25-28.
[9]王健琪,王海滨,杨国胜,荆西京,杨波,董秀珍,邱立军.心冲击图的雷达式非接触检测技术研究[J].北京生物医学工程,2001,20(2)：112-113.
[10]Chuang HR, Devedra M, Wang H, Postow E. An X-band microwave life-detection systems[J]. IEEE Trans Biomed Eng,1986,33(7):697-701.
[11]路国华,王健琪,杨国胜,王海滨,荆西京,邱力军,杨波.一种人体生命体征检测的新方法[J].北京生物医学工程,2001,20(4)：275-278.
[12]严登俊,李伟,王贵琴.生物电磁学研究进展[J].电气电子教学学报,2007,29(3)：11-16.
[13]Thayaparan T, Abrol S, Riseborough E. Micro-Doppler radar signatures for intelligent target recognition[R]. technical memorandum DRDC Ottawa:TM, 2004,23(2):165-170.
[14]Chen V C. Spatial and Temporal Independent Component Analysis of Micro-Doppler Features[R]. U.S. Government work not protected by U.S. copyright.
[15]崔来友,白士红,张春林等.人体运动学模型的研究[J].机械设计与研究,2003,19(6)：10-13.
[16]郭巧.现在机器人学[M].北京：北京理工大学,1997.
[17]Boashash B.Time-Frequency Signal Analysis and Processing[M]. Amsterdam: ELSEVIER Ltd,2003,23:577-626.
[18]L·科恩,时-频分析：理论与应用[M].中国西安：西安交通大学出版社,1998.
[19]Boashash B, Sucic V. Resolution measure criteria for the objective assessment of the performance of quadratic time-frequency distributions[J]. IEEE Transactions on signal processing,2003,51(5):1253-1263.
[20]Lovell B. C, Williamson R. C and Boashash B. The relationship between instantaneous frequency and time-frequency representations[J]. IEEE Transactions on Signal Processing,1993,41(3):1458-1461.
[21]Ram S. S, Ling H. Simulation of Human MicroDopplers Using Computer Animation Data[C]. IEEE Conference on Radar,2008.
[22]Smith G E, Woodbridge K, Baker C J. Multistatic Micro-Doppler Signature Of Personnel[C]. IEEE Conference on Radar,2008.
[23]Lei J. J, Lu C. Target classification based on micro-Doppler signatures[C]. In: Proceedings of IEEE International Conference on Radar. Washington, USA, May 2005,23(4):179-183.
[24]Michael G, Anderson R L R. Micro-Doppler analysis of multiple frequency continuous wave radar signature[C]. Radar Sensor Technology XI:Proc. of SPIE, 2007.
[25]Aggelopoulos E, Karabetsos E, Uzunoglu N, et al. Microwave System for the Detection of Trapped Human Beings[J]. Proceedings of the IEEE International Symposium on Industrial Electronics,1995,1:187-192.
[26]Stove A. G, Sykes S. R. A Doppler-based automatic target classifier for a battlefield surveillance radar[J]. Proceedings of IEEE International Conference on Radar. Edinburgh, UK, October 2002,45:419-423.
[27]Otero M. Application of a continuous wave radar for human gait Recognition[R]. SPIE Proceedings of the Signal Processing, Sensor Fusion, and Target Recognition XIV,2005,5809:538-548.
[28]史林,姜敏,黄莉.基于谐波模型的生命探测雷达人体状态识别方法[J].西安电子科技大学学报(自然科学版),2005,32(2)：1 79-1 83.
[29]闫冯军,朱家兵.基于宽带调频的非接触式探人雷达信号检测[J].中国科技信息,2007,12：303-304.
[30]王健琪,王海滨,荆西京等.呼吸、心率的雷达式非接触检测系统设计与研究
[J].中国医疗器械杂志,2001,25(3)：132-135.
[3l]路国华,王健琪,杨国胜等.一种人体生命体征检测的新方法[J].北京生物医学工程,2001,20(4)：275-278.
[32]路国华,王健琪,杨国胜等.非接触生命体征检测系统中噪声的非线性压缩[J].中国医疗器械杂志,2001,25(6)：316-317.
[33]张翼.人体微动雷达特征研究[D].长沙国防科技大学博士学位论文,2008.
[34]严登俊,李伟,王贵琴等.生物电磁学研究进展[J].电气电子教学学报,2007,29(3)：11-16.
[35]薛园园.USB应用技术开发大全[M].北京：人民邮电出版社,2007.
[36]金炯泰,金奎焕.如何使用KEIL 8051 C编译器[M].北京：北京航空航天大学出版社,2002.
[37]胡晓军.开发WDM型USB设备客户驱动程序[J].中国数据通信,2002,2：51-53.
[38]孙鑫,余安萍.VC++深入详解[M].北京：电子工业出版社,2006.
[39]张颖,张长利,基于DSP的具有以太网接口的嵌入式系统设计[J],煤矿机械,2005.
[40]曲延滨,冯立国,苏健勇,DSPTMS320VC5402的以太网接口设计[J],微处理机,2004.
[4l]彭启琮,管庆.DSP集成开发环境：CCS及DSPBIOS的原理与应用[M].北京：电子工业出版社,2004.
[42]Boulic R, Magnenat-thalmann N, Thalmann D. A global human walking model with real-time kinematic personification[J]. The Visual Computer,1990,253(5): 344-358.
[43]Michael G. Anderson, Robert L. Rogers. Micro-Doppler analysis of multiple frequency continuous wave radar signatures, Radar Sensor Technology XI, edited by James L. Kurtz, Robert J. Tan, Proc. of SPIE Vol.6547,65470A, (2007).
[44]刘冰啸.虚拟环境下的人体运动建模与仿真方法研究[D].中国科学技术大学硕士学位论文,2005.
[45]绳涛.仿人机器人力信息反馈控制方法研究[D].长沙：国防科技大学硕士学位论文,2005.
[46]郭巧.现在机器人学[M].北京：北京理工大学,1997.
[47]Geisheimer J L, Greneker E, Marshall W S. A high-resolution Doppler model of human gait[C]. Proceedings of SPIE on Radar Technology,2002.365:8-18.