生物雷达目标信息识别技术的实验研究
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摘要
生物雷达是一种用来探测生命体的特殊雷达,它融合了雷达技术和生物医学工程技术于一体,不需要任何电极或传感器接触生命体、间隔一定的距离、可穿透非金属介质(砖墙、废墟等)探测到生命体(人体)的生命信号(呼吸、体动等),该技术在战时和平时得到广泛的应用,如军事医学(伤员搜救)、灾害医学(地震或塌方后伤员的探寻)等领域。
在上述应用场合不仅关注是否探测到目标(人体)的存活,而且关注目标的状况,如目标的种类、数量、距离等信息。课题组研制的连续波生物雷达,已经较好地解决了目标存活的计算机智能判别,但是未能有效地解决两个主要存在的问题:1、目标信息的计算机识别,这些信息包括目标的种类(人或动物)、目标数量(单人或多人)等;2、目标距离信息的探测。本研究基于上述两个问题进行了以下几方面的工作:
1、采集了目标信息相关的实验数据(包括人与动物、单人与多人条件下的呼吸信号),采用功率谱估计和谱图变换技术对上述实验数据进行目标信号特征的分析,找出不同目标、同一目标不同数量条件下信号特征之间的差异性,为目标信息的计算机识别提供数据;
The bioradar is the result of the combination of radar technology and biomedical technology, which can be used to detect the lifeform parameters signals such as respiration and body-movement of the living objects like human beings, without any sensor or electrode touching the body at some distance. The technology can be widely used during the wartime and peacetime in the field such as military medicine to search the wounded soldiers, emergency medicine to locate the wounded people buried in the debris after earthquake or ruins.We not only pay attention to telling the target whether is living or not, but mor information such as the distance between the human beings and the bioradar, the difference between the human beings and animals and different numbers of people in the applied occasions described above. The continuous wave (CW) bioradar made by our team can automatically tell whether the target is living or not with an intelligent algorithm, but there exists two main problems. First, it cannot automatically identify the target information, including whether the target is human beings or animals and one person or more. Second it cannot
measure the distance between the target and the bioradar. According to these two problems existing in the CW bioradar made by our team, following studies and experiments have been performed in the paper:1. Achieving the experimental data by detecting the respiraion signal in the different conditions of human beings or dogs and different numbers of people, and analysing the feature of the data with the techonology of power spectral density (PSD) estimation and spectrogram transform (SPT) to find the difference existing in the target information detected by the CW bioradar made by our team, which can provide the data source to identify and classify the target informationn. 2. Selecting the technology of statistical pattern recognition (STPR) based on singular value decomposion (SVD) to extract the mode feature vectors and minimum distance classifier (MDC) to automatically recognize the target information. 3. Designing and developing the experimental bioradar based on the technology of ultra-wide band (UWB) radar to range the human subject, and making some experiments including detecting the lifeform parameters such as respiration and body-movement signal of a human subject in free space or penetrating the walls.The main results that have been accomplished in the paper are listed below: 1 .Provided the method of spectrogram transform to extract the feature vectors of the detecting subject to be the basis of target information recognition. 2. Provide the method of STPR based on SVD and MDC to identify the human beings from animals or one person from more. 3. Developed the experimental bioradar based on UWB to range the subject using its range gating technology.Innovations in the paper are listed below: 1 .Provided the method of STPR based on SPT and SVD to make the computer automaticaly recognize the target information detected by the bioradar, including the target whether is human
在上述应用场合不仅关注是否探测到目标(人体)的存活,而且关注目标的状况,如目标的种类、数量、距离等信息。课题组研制的连续波生物雷达,已经较好地解决了目标存活的计算机智能判别,但是未能有效地解决两个主要存在的问题:1、目标信息的计算机识别,这些信息包括目标的种类(人或动物)、目标数量(单人或多人)等;2、目标距离信息的探测。本研究基于上述两个问题进行了以下几方面的工作:
1、采集了目标信息相关的实验数据(包括人与动物、单人与多人条件下的呼吸信号),采用功率谱估计和谱图变换技术对上述实验数据进行目标信号特征的分析,找出不同目标、同一目标不同数量条件下信号特征之间的差异性,为目标信息的计算机识别提供数据;
The bioradar is the result of the combination of radar technology and biomedical technology, which can be used to detect the lifeform parameters signals such as respiration and body-movement of the living objects like human beings, without any sensor or electrode touching the body at some distance. The technology can be widely used during the wartime and peacetime in the field such as military medicine to search the wounded soldiers, emergency medicine to locate the wounded people buried in the debris after earthquake or ruins.We not only pay attention to telling the target whether is living or not, but mor information such as the distance between the human beings and the bioradar, the difference between the human beings and animals and different numbers of people in the applied occasions described above. The continuous wave (CW) bioradar made by our team can automatically tell whether the target is living or not with an intelligent algorithm, but there exists two main problems. First, it cannot automatically identify the target information, including whether the target is human beings or animals and one person or more. Second it cannot
measure the distance between the target and the bioradar. According to these two problems existing in the CW bioradar made by our team, following studies and experiments have been performed in the paper:1. Achieving the experimental data by detecting the respiraion signal in the different conditions of human beings or dogs and different numbers of people, and analysing the feature of the data with the techonology of power spectral density (PSD) estimation and spectrogram transform (SPT) to find the difference existing in the target information detected by the CW bioradar made by our team, which can provide the data source to identify and classify the target informationn. 2. Selecting the technology of statistical pattern recognition (STPR) based on singular value decomposion (SVD) to extract the mode feature vectors and minimum distance classifier (MDC) to automatically recognize the target information. 3. Designing and developing the experimental bioradar based on the technology of ultra-wide band (UWB) radar to range the human subject, and making some experiments including detecting the lifeform parameters such as respiration and body-movement signal of a human subject in free space or penetrating the walls.The main results that have been accomplished in the paper are listed below: 1 .Provided the method of spectrogram transform to extract the feature vectors of the detecting subject to be the basis of target information recognition. 2. Provide the method of STPR based on SVD and MDC to identify the human beings from animals or one person from more. 3. Developed the experimental bioradar based on UWB to range the subject using its range gating technology.Innovations in the paper are listed below: 1 .Provided the method of STPR based on SPT and SVD to make the computer automaticaly recognize the target information detected by the bioradar, including the target whether is human
引文
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[2] K. M. Chen, Y. Huang, A. Norman and J. Zhang. Microwave Life-Detection System for detecting human subjects through barriers[J]. Progress in Electromagnetic Research Symp. Hong Kong. 1997, 1: 6-9
[3] Droitcour AD, Lubecke VM and Lin J, et. al A Microwave Radio for Doppler Radar Sensing of Vital Signs[C]. 2001 IEEE MTT-S International Microwave Symposium. 2001, 1: 175-178.
[4] Droitcour AD, Boric-Lubecke O and Libecke VM, et. al.0.25um CMOS and BiCMOS Single-chip Direct-conversion Doppler Radars for Remote Sensing of Vital Signs[C]. 2002 ISSCC Digest. 2002, 1: 348-348.
[5] Droitcour AD, Boric-Lubecke O and Lubecke VM, et. al. Range Correlation Effect on ISM Band I/Q CMOS Radar for Non-Contact Cardiopulmonary Monitoring[C]. 2003 IEEE MTT-S IMS Digest, Philadelphis. 2003, 3: 1945-1948.
[6] 王健琪,董秀珍等.基于毫米波的呼吸、心跳非接触检测实验研究[J].第四军医大学学报2001;22(2):175—177
[7] 王健琪,王海滨等.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2001,21(5):112-114
[8] 倪安胜.伤员探测中生命体识别技术研究[D].第四军医大学硕士论文.2003
[9] Caro CG and Bloice JA. Contactless apnea detector based on radar[J]. Lancet 1971, 2(7731): 959-961
[10] Franks CI and Bloice JA. Contactless respiration monitoring of infants[J]. Med. Biol. Eng. 1976, 14(3): 306-318
[11] Franks CI, Watson JB and Foster EF. Respiration patterns and risk of sudden unexpected death in infancy[J]. Arch. Dis. Child 1980, 55(8): 595-604
[12] D. K. Misra. Scattering of electromagnetic waves by human body and its applications [D]. Ph. D. dissertation, Michigan State Univ., East Lansing, 1984.
[13] Yoshio Yamaguchi, Masashi Mitsumoto, Masakazu Sengoku and Takeo Abe. Synthetic Aperture FM-CW Radar Applied to the Detection of Objects Buried in Snowpack [J]. IEEE Transaction on Geoscience and Remote Sensing. 1994, 32(1): 11-18
[14] J. F. Holzdchter, G. C. Bumett, L. C. Ng and W. A. Lea. Speech Articulator Measurements Using Low Power EM-wave[J]. Journal of Acoustical Society of America. 1998, 103(1): 622-625
[15] 本村和磨,荒井郁男.24GHz波心拍开発[J].医用電子生体工学1997,35(3):17-23
[16] Huey-Ru Chuang, Y. -F. Chen, Kun-Mu Chen. Automatic Clutter-Canceler for Microwave Life-Detection Systems [J]. IEEE Transaction on Instruments and Measurement, 1991; 40(4): 747-750
[17] Kun-Mu Chen, YongHuang, JianPing Zhang, Adam Norman. Microwave Life-Detection System for Searching Human Subjects Under Earthquake Rubble or Behind Barrier[J]. IEEE Trans Biomed Eng. 2000, 27(1): 105-114
[18] wang jian-qi, zheng chong-xun, jing xi-jing, lu guo-hua, wang hai-bin. Study on a No-contact life parameter detection system using millimeter wave. SPACE MEDICINE & MEDICAL ENGINEERING. 2004; 17(3): 157-161
[19] http://www.getradar.com/AboutUs.htm
[20] Mieropower Impulse Radar[R]. Scienceand Technology Review. UCRL-52000-96-1/2.
[21] McEwan. Body monitoring and imaging apparatus and method [P]. 1996, United States Patent 5, 573, 208
[22] McEwan. Body monitoring and imaging apparatus and method [P]. 1998, United States Patent 5, 766, 208
[23] Enrico M. Staderini. UWB radars in medicine [J]. IEEE Aerospace and Electronic Systems Magazine, 2002, 1: 13-18
[24] http://www.uwb.org
[25] Immoreev IJ, Samkov SV. Ultra-wideband (UWB) radar for remote measuring of main parameters of patient's vital activity [J]. Radio physics and Radio astronomy(Ukraine), 2002; 7(4): 404-407
[26] 王晓丹,王积勤.雷达目标识别技术综述[J].现代雷达.2003,5:22-26
[27] 韩艳春,李智兰,曾宪文.目标识别与分类方法[J].军事通信技术.2003,24(1):61-63
[28] 杜亚娟,潘泉,张洪才.雷达目标识别方法概述[J].火控雷达技术.1998,27(12):1-5
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