主动电磁波生命信号实时检测处理技术研究
|
摘要
主动电磁波生命信号的实时检测处理是利用生命体对电磁波产生的多普勒效应,提取电磁波回波中的生命信号进行人体状态识别。根据人体的呼吸、心跳等生理特征,从主动发射电磁波的目标反射回波中,可以判别出人体有/无、动/静以及数量等信息。主动电磁波的生命信号探测方法,克服了传统的探生设备容易受外界环境限制和干扰的缺点,抗干扰能力强,适用于地震、塌方、山体滑坡等灾害后对受困人员的及时营救,同时也可用于医疗看护、狱所监管及反恐作战等领域,具有重要的应用价值。
生命信号属于低速慢变信号,所产生的多普勒频移小。在灾后杂乱环境中检测生命体,回波信号微弱极易淹没于强杂波背景。如何有效地检测和提取出所需的微弱目标信号(即生命特征信号),以及识别出人体有/无、动/静以及数量等状态信息是论文的研究重点。
本文根据小波变换的多分辨率特性,选取了d4小波,在噪声背景下检测和提取生命信号,采用呼吸与体动信号能量比、谐波参数估计及维格纳分布等方法,通过设置合适的处理门限值,自动完成人体状态信息的识别。该处理算法的综合处理能力强,实用性好,能够完成人体有/无、动/静以及数量等状态信息的判别,可以为操作人员提供直观、准确的信息。
基于所研究的生命信号检测处理算法,设计了生命信号的实时检测处理系统。系统的硬件系统构成是分别以AD转换芯片AD7707和DSP处理芯片TMS320C6711B为核心,完成信号的解调和实时采集、传输及处理。该硬件系统设计电路功能合理,运行状态稳定,处理能力较强。基于TMS320C6711B高性能浮点DSP芯片,实现了数据的高速传输、实时处理和显示,使系统不仅体积小巧,抗干扰能力和探测能力等较之以C5000系列为DSP处理芯片的处理系统,均有所提高,并且为软件程序的稳定运行搭建一个良好平台。
基于TMS320C6711B的生命信号实时检测处理系统,在CCS集成开发环境下完成了DSP的控制与实时检测处理软件程序的设计,主要包括生命信号实时检测处理算法的DSP软件设计与实现,以及Bootloader、系统初始化、中断服务、串口通讯、FIR滤波、FFT等程序的设计。该DSP部分的软件程序设计合理,能高效、实时的对生命信号进行采集处理,较好地实现了整个系统的控制和数据处理功能,并且实时显示出人体状态和数量等详细信息以及时频域的波形图。
The technology of real-time detecting and processing active electromagnetic life signal is mainly based on the principle of Doppler frequency shifting. When the Electromagnetic wave was reflected by the body, we can extract life relevant characteristics information from the echo after properly being processed. Since signal was modulated by human life activities, such as breathing, heartbeating, etc, some parameters of the signal were changed. From the echo signal, we can estimate whether life is alive, active and the number of lives. The tradional life-detection equipments are always limited due to the external complicated environment, however,the method of real-time detecting and processing active electromagnetic life signal have the better anti-interference capability. This method is worth greater application, It not only can rescue injured persons quickly after earthquakes, collapse, mountain avalanche, and other disasters, but also can be used to medical care, prison surveillance as well as anti-terrorism fields and so on.
Life signals are low-velocity and slow-change target signals with very small Doppler frequency shifts and so weak that echo signals were easily submerged in the serious clutter and noise. The key in this paper is to detect and extract the weak target signal, and recognize whether life is alive,active and the number of lives availably.
This thesis designs a series of methods to recognize life signal from the echo. Firstly, the d4 wavelet which is based on the muti- resolution characteristic of wavelet transform was proposed to detect and extract life signal in the noise background. Secondly, the energy ratio of breathing and movement, parameters estimating of wave resonance and WD(Wigner Distribution)were designed to distinguish life relevant characteristics information automatically. This method has high efficiency and good practicability, and can provide the intuitionistic and credible information for the operator.
Based on the designed algorithm framework, the life signal real-time detecting and processing system was designed. The kernel of the hardware part of the system is AD7707 and TMS320C6711B. The system can realize the high-speed transmiting, real-time processing and displaying of the data. It is not only tiny and compact, but also have better anti-interference and detecting ability. Moreover, it can provide the well hardware plat for the stable software running.
Based on the TMS320C6711B, the software part of the system is designed under the CCS development software, which contains design and realization of DSP software, as well as code design of Bootloader, system initializing, interrupt service, data communication, FIR filtering, FFT and so on. The software codes of DSP part were designed reasonably, which make the life signal collecting and processing efficiently. It realized system control and data processing, and real-time display of results, as well as time-frequency waveform figures.
生命信号属于低速慢变信号,所产生的多普勒频移小。在灾后杂乱环境中检测生命体,回波信号微弱极易淹没于强杂波背景。如何有效地检测和提取出所需的微弱目标信号(即生命特征信号),以及识别出人体有/无、动/静以及数量等状态信息是论文的研究重点。
本文根据小波变换的多分辨率特性,选取了d4小波,在噪声背景下检测和提取生命信号,采用呼吸与体动信号能量比、谐波参数估计及维格纳分布等方法,通过设置合适的处理门限值,自动完成人体状态信息的识别。该处理算法的综合处理能力强,实用性好,能够完成人体有/无、动/静以及数量等状态信息的判别,可以为操作人员提供直观、准确的信息。
基于所研究的生命信号检测处理算法,设计了生命信号的实时检测处理系统。系统的硬件系统构成是分别以AD转换芯片AD7707和DSP处理芯片TMS320C6711B为核心,完成信号的解调和实时采集、传输及处理。该硬件系统设计电路功能合理,运行状态稳定,处理能力较强。基于TMS320C6711B高性能浮点DSP芯片,实现了数据的高速传输、实时处理和显示,使系统不仅体积小巧,抗干扰能力和探测能力等较之以C5000系列为DSP处理芯片的处理系统,均有所提高,并且为软件程序的稳定运行搭建一个良好平台。
基于TMS320C6711B的生命信号实时检测处理系统,在CCS集成开发环境下完成了DSP的控制与实时检测处理软件程序的设计,主要包括生命信号实时检测处理算法的DSP软件设计与实现,以及Bootloader、系统初始化、中断服务、串口通讯、FIR滤波、FFT等程序的设计。该DSP部分的软件程序设计合理,能高效、实时的对生命信号进行采集处理,较好地实现了整个系统的控制和数据处理功能,并且实时显示出人体状态和数量等详细信息以及时频域的波形图。
The technology of real-time detecting and processing active electromagnetic life signal is mainly based on the principle of Doppler frequency shifting. When the Electromagnetic wave was reflected by the body, we can extract life relevant characteristics information from the echo after properly being processed. Since signal was modulated by human life activities, such as breathing, heartbeating, etc, some parameters of the signal were changed. From the echo signal, we can estimate whether life is alive, active and the number of lives. The tradional life-detection equipments are always limited due to the external complicated environment, however,the method of real-time detecting and processing active electromagnetic life signal have the better anti-interference capability. This method is worth greater application, It not only can rescue injured persons quickly after earthquakes, collapse, mountain avalanche, and other disasters, but also can be used to medical care, prison surveillance as well as anti-terrorism fields and so on.
Life signals are low-velocity and slow-change target signals with very small Doppler frequency shifts and so weak that echo signals were easily submerged in the serious clutter and noise. The key in this paper is to detect and extract the weak target signal, and recognize whether life is alive,active and the number of lives availably.
This thesis designs a series of methods to recognize life signal from the echo. Firstly, the d4 wavelet which is based on the muti- resolution characteristic of wavelet transform was proposed to detect and extract life signal in the noise background. Secondly, the energy ratio of breathing and movement, parameters estimating of wave resonance and WD(Wigner Distribution)were designed to distinguish life relevant characteristics information automatically. This method has high efficiency and good practicability, and can provide the intuitionistic and credible information for the operator.
Based on the designed algorithm framework, the life signal real-time detecting and processing system was designed. The kernel of the hardware part of the system is AD7707 and TMS320C6711B. The system can realize the high-speed transmiting, real-time processing and displaying of the data. It is not only tiny and compact, but also have better anti-interference and detecting ability. Moreover, it can provide the well hardware plat for the stable software running.
Based on the TMS320C6711B, the software part of the system is designed under the CCS development software, which contains design and realization of DSP software, as well as code design of Bootloader, system initializing, interrupt service, data communication, FIR filtering, FFT and so on. The software codes of DSP part were designed reasonably, which make the life signal collecting and processing efficiently. It realized system control and data processing, and real-time display of results, as well as time-frequency waveform figures.
引文
[1] A.S.Bugaev,Through Wall Sensing of Human Breathing and Heart Beating by Monochromatic Radar[A]. Tenth International Conference on Ground penetrating Radar,21-24June,2004,pp:291-294
[2] David.D.Ferris,NicholasC.Currie. A survey of current technologies for through-the-wall surveillance[C]. Conference on Sensors,1998
[3] D.Misra,K.M.Chen. Responses of electric-field probes near a cylindrical model of the human body[C] . Theory and Tech,1995
[4]游林儒,吴庆家,文小琴.基于超低频电磁波的穿墙生命探测技术[J].传感器与微系统,2008
[5]王绪本,郭勇,王娇.基于声波与振动探测的地震灾害生命搜索系统信号分析[C].工程地球物理学报,2005
[6]叶勇,王健琪.基于DSP的非接触生命探测系统中信号处理单元的研制[J].医疗卫生装备,2005.3
[7]林生,孙强.现代隔墙探测技术扫描[J].军事工程,2006
[8]余晶,周觅.穿墙雷达中的多目标探测研究[C].成都信息工程学院学报,2008
[9]宋华,李禹.超宽带穿墙探测雷达的运动目标检测技术[J].电讯技术,2004
[10] Borek,S.e.(Air Force Research Laboratory ). An overview of through the wall surveillance for homeland security [A]. IEEE,19-21.Oct.2005.Proceedings of the 34th Applied. Imagery and pattern Recognition workshop:42-47
[11] Alexander S. Bugaev,Mathematical Simulation of Remote Detection of Human Breathing and Heartbeat by Multifrequency Radar on the Background of Local Objects Reflections[C]. 2005
[12] Kun-Mu Chen. Microwave Life-Detection Systems for Searching Human Subjects Under Earthquake Rubble or Behind Barrier[C]. IEEE Trans actions on biomedical eningeering,2000
[13] Huey-Ru Chuang,Chen Y.F,Kun-Mu. Automatic Clutter-Canceler for Microwave Life-Detection Systems.Instrumentation and Measurement[C]. IEEE Transaction on,1991
[14]李刚. LFMCW生命探测雷达信号处理技术研究[D].西北工业大学硕士学位论文,2007
[15]邱力军,董秀珍.生命探测系统中频信号的采样准则和频谱特性[J].第四军医大学学报,2003
[16] David.D.Ferris,Jr.Nicholas C. Currie (Air Force Research Laboratory ) A surve of current technologies for through–the-wall surveillance (TWS) [J]. Proc,SPIE,Now.1998,vol.3577:62-72
[17] A.A.Vertiy,L.V.Voynov sky,sunullah Ozbek.Microwave through-obstacles life-signs detection system.The Remoto sensing Laboratory Annual,2005.12,20
[18]孙元敏.基于DSP的数据采集处理系统的设计与实现[D].山东大学硕士学位论文,2008
[19]罗漫江.生命探测仪的技术研究[D].西安电子科技大学,2004
[20] David.D.Ferris,NicholasC.Currie Microwave and millimeter-wave systems for wall penetration[C],1998
[21]史林,姜敏.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,2005
[22] Mehrdad Soumekh signal processing of wide bandwidth and wide beamwidth p-3 SAR data.IEEE Transactions on Volume 37,Issue,Oct.2001.p1122-1141
[23] Sweldens W. The lifting scheme:A custom design constrotion for biothogonal wavelets Technical Report,University of South Carolina,1994,1~39
[24] Daubechies I,Sweldens W. factoring wavelet transforms into lifting steps.J.Fourier Anal.Appl,1998,4(3):247~269E.G
[25]杨东.基于非接触生命参数检测系统的信号处理技术研究[D].第四军医大学学位论文,2005
[26] Yoo H,Jeony J,A unified framework for wavelet transfoems based on the Lifting scheme. IEEE Trans,2001
[27]黄莉,史林.基于提升算法的低速目标信号提取与生命信号检测应用[J].电子科技,2004
[28]李杰,王健琪,荆西京,谢昇,路国华,张杨.非接触生命参数检测系统动/静目标的识别技术[J].第四军医大学学报,2005
[29] Chen Kunmu,Huang Yong,Zhang Jianping. Microwave life-detection Systems for Searching Human Subjects under Eatthquake Rubble or Behind Barrier[J]. IEEE Trans on Biomed Eng,2000.27(1):105-114
[30] Kay,S.M.and.S.L.Marple,“Spectrum Analysis-A modern Perspective,”Proc IEEE,Vol.69,pp.1380-1418,198
[31] Swami A,Mendel JM,Cummulant-based approach to the harmonic retrieval and recated problems.IEEE Trans.Signal processing,1991,39:1099-1109
[32]张贤达.现代信号处理[M].北京:清华大学出版社,2002.J
[33]牛犇.生命探测雷达信号识别方法研究[D].西安电子科技大学硕士学位论文,2006
[34] Yanming Xiao. Frequency-Tuning Technique for Remote Detection of Heartbeat and Respiration Using Low-Power Double-Sideband Transmission in the Ka-Band[C],2006
[35] [美]L.科恩著.自居宪译.时-频分析:理论与应用[M].西安:西安交通大学出版社,1998
[36]柴新禹,吴朝霞,等.时频分析方法及其在医学信号处理中的应用[J].医疗卫生装备,2006.6
[37]路国华,杨国胜,王健琪,荆西京.雷达式生命探测仪中人体数量识别技术的研究[J].北京生物医学工程,2005
[38]皇甫堪,陈建文,楼生强.现代数字信号处理[M].电子工业出版社,2004
[39]程云鹏,张凯院,徐仲,等.矩阵论[M].西安:西北工业大学,1989.6
[40]蔡立羽,王志中,张海虹.基于短时傅里叶变换的肌电信号识别方法[J].中国医疗器械杂志,2000,24(3):133—37
[41] J.ville,〞Theorie et applications delanotion designal analytuque,〞Cables et transmissions,vol.2A,pp.61-74,1948.Translated from French by I.Selin,〞Theory and applications of the notion of complex signal,〞RAND Corporation Technical Report T-92,Santa Monica,CA,1958
[42] Cadzow JA.Spectrum estimation:An overdetrmined ration model equation approach.Proc.IEEE,1982,70:907-938
[43]詹鹏.DSP在雷达生命探测系统中的应用研究[D].成都理工大学硕士学位论文,2008
[44] A.Izadi,Design and Simulation of a Life Detection System Based on Detection of the Heart Beat Using Dopler Frequency[C]. 2006
[45] Analog Devices. AD7707 Data Sheet. 2000
[46]叶勇.基于DSP的雷达式非接触生命探测仪信号处理系统研制[D].第四军医大学硕士学位论文,2005
[47]叶勇,王健琪,焦腾,穆飞航.基于AD7707芯片的数据采集系统设计[J].第四军医大学学报,2005
[48]潘旭兵,林中.嵌入式Linux下AD7707驱动程序的设计[J].单片机与嵌入式系统应用,2007.6
[49]任丽香,马淑芬,等.TMS320C6000系列DSP的原理与应用[M].北京:电子工业出版社,2001
[50] TMS320C6711B/C/D Floating-doing Digtal Signal Pressors[P]. Texas Instruments Incorported,2003
[51]章飚,丁国辉.TMS320C6000DSP芯片的外围高速电路设计[D].测控技术,2004
[52] TMS320C6000 EMIF-to-External SDRAM Interface[P]. Texas Instruments Incorported,2003
[53] TMS320C6000 EMIF-to-External Flash Memory[P]. Texas InstrumentsIncorported,2003
[54] MAX3111E Data Sheet. Analog Devices 1998.
[55] Texas Instrument Incorporated著,彭启琮等编译.TI DSP集成化开发环境(CCS)使用手册[M].清华大学出版社,2005
[56] Texas Instruments Incorporated. Code Composer Studio Tutorial,2001
[57]李建军.生命探测雷达信号处理算法研究[D].西安电子科技大学硕士学位论文,2006
[58]郑争兵.基于DSP的串行通信接口设计[J].测试测量技术,2008
[59]苏涛,等.实时信号处理系统设计[M].西安电子科技大学出版社,2006
[2] David.D.Ferris,NicholasC.Currie. A survey of current technologies for through-the-wall surveillance[C]. Conference on Sensors,1998
[3] D.Misra,K.M.Chen. Responses of electric-field probes near a cylindrical model of the human body[C] . Theory and Tech,1995
[4]游林儒,吴庆家,文小琴.基于超低频电磁波的穿墙生命探测技术[J].传感器与微系统,2008
[5]王绪本,郭勇,王娇.基于声波与振动探测的地震灾害生命搜索系统信号分析[C].工程地球物理学报,2005
[6]叶勇,王健琪.基于DSP的非接触生命探测系统中信号处理单元的研制[J].医疗卫生装备,2005.3
[7]林生,孙强.现代隔墙探测技术扫描[J].军事工程,2006
[8]余晶,周觅.穿墙雷达中的多目标探测研究[C].成都信息工程学院学报,2008
[9]宋华,李禹.超宽带穿墙探测雷达的运动目标检测技术[J].电讯技术,2004
[10] Borek,S.e.(Air Force Research Laboratory ). An overview of through the wall surveillance for homeland security [A]. IEEE,19-21.Oct.2005.Proceedings of the 34th Applied. Imagery and pattern Recognition workshop:42-47
[11] Alexander S. Bugaev,Mathematical Simulation of Remote Detection of Human Breathing and Heartbeat by Multifrequency Radar on the Background of Local Objects Reflections[C]. 2005
[12] Kun-Mu Chen. Microwave Life-Detection Systems for Searching Human Subjects Under Earthquake Rubble or Behind Barrier[C]. IEEE Trans actions on biomedical eningeering,2000
[13] Huey-Ru Chuang,Chen Y.F,Kun-Mu. Automatic Clutter-Canceler for Microwave Life-Detection Systems.Instrumentation and Measurement[C]. IEEE Transaction on,1991
[14]李刚. LFMCW生命探测雷达信号处理技术研究[D].西北工业大学硕士学位论文,2007
[15]邱力军,董秀珍.生命探测系统中频信号的采样准则和频谱特性[J].第四军医大学学报,2003
[16] David.D.Ferris,Jr.Nicholas C. Currie (Air Force Research Laboratory ) A surve of current technologies for through–the-wall surveillance (TWS) [J]. Proc,SPIE,Now.1998,vol.3577:62-72
[17] A.A.Vertiy,L.V.Voynov sky,sunullah Ozbek.Microwave through-obstacles life-signs detection system.The Remoto sensing Laboratory Annual,2005.12,20
[18]孙元敏.基于DSP的数据采集处理系统的设计与实现[D].山东大学硕士学位论文,2008
[19]罗漫江.生命探测仪的技术研究[D].西安电子科技大学,2004
[20] David.D.Ferris,NicholasC.Currie Microwave and millimeter-wave systems for wall penetration[C],1998
[21]史林,姜敏.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,2005
[22] Mehrdad Soumekh signal processing of wide bandwidth and wide beamwidth p-3 SAR data.IEEE Transactions on Volume 37,Issue,Oct.2001.p1122-1141
[23] Sweldens W. The lifting scheme:A custom design constrotion for biothogonal wavelets Technical Report,University of South Carolina,1994,1~39
[24] Daubechies I,Sweldens W. factoring wavelet transforms into lifting steps.J.Fourier Anal.Appl,1998,4(3):247~269E.G
[25]杨东.基于非接触生命参数检测系统的信号处理技术研究[D].第四军医大学学位论文,2005
[26] Yoo H,Jeony J,A unified framework for wavelet transfoems based on the Lifting scheme. IEEE Trans,2001
[27]黄莉,史林.基于提升算法的低速目标信号提取与生命信号检测应用[J].电子科技,2004
[28]李杰,王健琪,荆西京,谢昇,路国华,张杨.非接触生命参数检测系统动/静目标的识别技术[J].第四军医大学学报,2005
[29] Chen Kunmu,Huang Yong,Zhang Jianping. Microwave life-detection Systems for Searching Human Subjects under Eatthquake Rubble or Behind Barrier[J]. IEEE Trans on Biomed Eng,2000.27(1):105-114
[30] Kay,S.M.and.S.L.Marple,“Spectrum Analysis-A modern Perspective,”Proc IEEE,Vol.69,pp.1380-1418,198
[31] Swami A,Mendel JM,Cummulant-based approach to the harmonic retrieval and recated problems.IEEE Trans.Signal processing,1991,39:1099-1109
[32]张贤达.现代信号处理[M].北京:清华大学出版社,2002.J
[33]牛犇.生命探测雷达信号识别方法研究[D].西安电子科技大学硕士学位论文,2006
[34] Yanming Xiao. Frequency-Tuning Technique for Remote Detection of Heartbeat and Respiration Using Low-Power Double-Sideband Transmission in the Ka-Band[C],2006
[35] [美]L.科恩著.自居宪译.时-频分析:理论与应用[M].西安:西安交通大学出版社,1998
[36]柴新禹,吴朝霞,等.时频分析方法及其在医学信号处理中的应用[J].医疗卫生装备,2006.6
[37]路国华,杨国胜,王健琪,荆西京.雷达式生命探测仪中人体数量识别技术的研究[J].北京生物医学工程,2005
[38]皇甫堪,陈建文,楼生强.现代数字信号处理[M].电子工业出版社,2004
[39]程云鹏,张凯院,徐仲,等.矩阵论[M].西安:西北工业大学,1989.6
[40]蔡立羽,王志中,张海虹.基于短时傅里叶变换的肌电信号识别方法[J].中国医疗器械杂志,2000,24(3):133—37
[41] J.ville,〞Theorie et applications delanotion designal analytuque,〞Cables et transmissions,vol.2A,pp.61-74,1948.Translated from French by I.Selin,〞Theory and applications of the notion of complex signal,〞RAND Corporation Technical Report T-92,Santa Monica,CA,1958
[42] Cadzow JA.Spectrum estimation:An overdetrmined ration model equation approach.Proc.IEEE,1982,70:907-938
[43]詹鹏.DSP在雷达生命探测系统中的应用研究[D].成都理工大学硕士学位论文,2008
[44] A.Izadi,Design and Simulation of a Life Detection System Based on Detection of the Heart Beat Using Dopler Frequency[C]. 2006
[45] Analog Devices. AD7707 Data Sheet. 2000
[46]叶勇.基于DSP的雷达式非接触生命探测仪信号处理系统研制[D].第四军医大学硕士学位论文,2005
[47]叶勇,王健琪,焦腾,穆飞航.基于AD7707芯片的数据采集系统设计[J].第四军医大学学报,2005
[48]潘旭兵,林中.嵌入式Linux下AD7707驱动程序的设计[J].单片机与嵌入式系统应用,2007.6
[49]任丽香,马淑芬,等.TMS320C6000系列DSP的原理与应用[M].北京:电子工业出版社,2001
[50] TMS320C6711B/C/D Floating-doing Digtal Signal Pressors[P]. Texas Instruments Incorported,2003
[51]章飚,丁国辉.TMS320C6000DSP芯片的外围高速电路设计[D].测控技术,2004
[52] TMS320C6000 EMIF-to-External SDRAM Interface[P]. Texas Instruments Incorported,2003
[53] TMS320C6000 EMIF-to-External Flash Memory[P]. Texas InstrumentsIncorported,2003
[54] MAX3111E Data Sheet. Analog Devices 1998.
[55] Texas Instrument Incorporated著,彭启琮等编译.TI DSP集成化开发环境(CCS)使用手册[M].清华大学出版社,2005
[56] Texas Instruments Incorporated. Code Composer Studio Tutorial,2001
[57]李建军.生命探测雷达信号处理算法研究[D].西安电子科技大学硕士学位论文,2006
[58]郑争兵.基于DSP的串行通信接口设计[J].测试测量技术,2008
[59]苏涛,等.实时信号处理系统设计[M].西安电子科技大学出版社,2006
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |