人体微动雷达特征研究
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摘要
人体的探测在安全防护、灾害救援、军事医学等领域有着广泛需求,其中利用电磁波对人体微动的提取与辨识研究日益受到重视。本论文针对人体步态下的肢体摆动对电磁波的调制作用、人体微多普勒特征分析、步态参数的估计、姿态参数的估计、运动模式的辨识等问题开展研究。
论文首先综述了人体微动雷达特征研究的发展现状,提出了需要研究的问题并对本论文研究内容进行了规划。
针对人体微动对电磁波的调制作用问题,在基于类人型机器人和虚拟人研究的基础上,提出了适用于人体雷达特征研究的人体线结构模型,分析了各肢体的运动学轨迹;在此基础上推衍出了人体行走状态雷达回波的解析表达式;运用时频分析手段提取了行人雷达回波中的微多普勒特征,研究了人体运动参数与微多普勒特征的关系,特别对人体规范行走中关键步态的微多普勒特征进行了研究。
针对估计人体行走参数的问题,深入研究了van Dorp P.提出的特征参数提取方法和人体步态参数估计方法,并应用于实测数据,提取了人体微动特征,估计了步态参数;研究了人体上肢姿态参数与多普勒特征的内在关系,提出了从行人上肢微多普勒特征中提取特征参数的方法,并用于估计上肢姿态参数;提出了基于函数逼近论原理的规范行走中人体下肢姿态参数的估计方法及实现途径。
针对人体运动辨识问题,提出了基于微多普勒特征分析和步态参数估计的分辨方法。首先分析了人体跑步的时空特性,将之与人体规范行走的时空特性进行分析与比较,在基于规范行走与跑步状态下人体微多普勒特征分析的基础上,提出了可用于进行运动辨识的特征;在对大量实测数据分析与实验的基础上,提出了以支撑矢量机作为分类器的人体运动分辨方法;深入研究了Otero M.提出的人体行走时频图分析方法,提出了一种单人和多人行走的分辨方法,探索了人和动物的分辨问题。
为了支撑论文上述研究工作,设计并研制了人体微动雷达测量系统,设计完成了相关数据测量实验并分析了结果。首先对雷达测量系统要求进行了剖析,设计了雷达系统的组成结构,着重分析了雷达回波采集系统的硬件设计与实现,而后提出了人体步态雷达测量的实验方案,完成了大量的实验数据采集,并对该系统存在的问题作出了说明,提出了下一步的改进目标。
最后,对论文工作和研究方向的发展趋势、应用前景进行了总结,指出了需要进一步研究和解决的问题。
Due to the complicated battlefield circumstance and the requirement of safety protection, disaster rescue, and military medical science, the study on the radar feature of human micro-motion is more and more highly regarded. This paper just studies the radar feature of human walking mode, the modulating function of limbs’swinging movement on the radar waves when walking, micro-Doppler feature analysis of human body, estimation of pace parameter, estimation of posture parameter, and identification of movement mode, etc.
The paper first described the present situation of radar feature study of human micro-motion, laid out the content of this paper and raised the issues that need research.
As for the modulating function of human micro-motion on radar wave, the paper raised human body linear structure model that is suitable for human body radar feature study based on the study of human-alike robot and virtual human, analyzed the kinematic track of each limb, deduced the radar echo of human walking and gave the resolution expression. Then, the paper extracted the micro-Doppler feature of walking human radar echo by applying time-frequency analysis means, studied the relationship between human motion parameter and micro-Doppler feature, and especially studied the micro-Doppler feature of key paces of human walking.
As for extraction of human walking feature, the paper deeply studied the methods of feature parameter extraction and human pace parameter estimation raised by P. van Dorp, and applied them in field-measured data and thus extracted human micro-motion feature and estimated pace parameter; the paper also studied the inner relationship between human upper limb posture parameter and micro-Doppler feature,raised the method of extracting feature parameter from the micro-Doppler feature of the upper limbs of walking human and applied it to estimate upper limb posture parameter; then the paper raised the method and approach of estimating the posture parameter of lower limbs of walking human based on function approximation theory.
As for human motion identification, the paper raised the distinguishing method based on micro-Doppler feature analysis and pace parameter estimation. The author firstly listed the time and space features of human running and compared them with those of normal human walking. Then, based on analysis of human micro-Doppler features during walking and during running, the paper raised the features that can be used in motion identification; based on analysis and experiment of plenty of field-measured data, the paper raised a human motion distinguishing method that applies the support vector machine as classifier. The paper also deeply studied the time-frequency chart analysis method for human walking raised by Michael Otero, raised a method for distinguishing single human walking and more-than-one-person walking, and explored the method of distinguishing human beings and animals.
Based on the study on the basis of a great amount of field-measured data, the paper introduced the establishment of radar measurement system and the analysis of experiment result. Firstly, the author analyzed the design requirement of radar measurement system, designed the composition structure of radar system, and stressed the hardware design and realization of radar echo collecting system; then the author raised the experiment plan of human pace radar measurement experiment and collected plenty of experiment data. The author also listed the problems that exist in the system and raised the improvement target in future research.
At last, the author summarized the developing trend and application prospect of the dissertation study and pointed out the problems that need further study and resolution.
论文首先综述了人体微动雷达特征研究的发展现状,提出了需要研究的问题并对本论文研究内容进行了规划。
针对人体微动对电磁波的调制作用问题,在基于类人型机器人和虚拟人研究的基础上,提出了适用于人体雷达特征研究的人体线结构模型,分析了各肢体的运动学轨迹;在此基础上推衍出了人体行走状态雷达回波的解析表达式;运用时频分析手段提取了行人雷达回波中的微多普勒特征,研究了人体运动参数与微多普勒特征的关系,特别对人体规范行走中关键步态的微多普勒特征进行了研究。
针对估计人体行走参数的问题,深入研究了van Dorp P.提出的特征参数提取方法和人体步态参数估计方法,并应用于实测数据,提取了人体微动特征,估计了步态参数;研究了人体上肢姿态参数与多普勒特征的内在关系,提出了从行人上肢微多普勒特征中提取特征参数的方法,并用于估计上肢姿态参数;提出了基于函数逼近论原理的规范行走中人体下肢姿态参数的估计方法及实现途径。
针对人体运动辨识问题,提出了基于微多普勒特征分析和步态参数估计的分辨方法。首先分析了人体跑步的时空特性,将之与人体规范行走的时空特性进行分析与比较,在基于规范行走与跑步状态下人体微多普勒特征分析的基础上,提出了可用于进行运动辨识的特征;在对大量实测数据分析与实验的基础上,提出了以支撑矢量机作为分类器的人体运动分辨方法;深入研究了Otero M.提出的人体行走时频图分析方法,提出了一种单人和多人行走的分辨方法,探索了人和动物的分辨问题。
为了支撑论文上述研究工作,设计并研制了人体微动雷达测量系统,设计完成了相关数据测量实验并分析了结果。首先对雷达测量系统要求进行了剖析,设计了雷达系统的组成结构,着重分析了雷达回波采集系统的硬件设计与实现,而后提出了人体步态雷达测量的实验方案,完成了大量的实验数据采集,并对该系统存在的问题作出了说明,提出了下一步的改进目标。
最后,对论文工作和研究方向的发展趋势、应用前景进行了总结,指出了需要进一步研究和解决的问题。
Due to the complicated battlefield circumstance and the requirement of safety protection, disaster rescue, and military medical science, the study on the radar feature of human micro-motion is more and more highly regarded. This paper just studies the radar feature of human walking mode, the modulating function of limbs’swinging movement on the radar waves when walking, micro-Doppler feature analysis of human body, estimation of pace parameter, estimation of posture parameter, and identification of movement mode, etc.
The paper first described the present situation of radar feature study of human micro-motion, laid out the content of this paper and raised the issues that need research.
As for the modulating function of human micro-motion on radar wave, the paper raised human body linear structure model that is suitable for human body radar feature study based on the study of human-alike robot and virtual human, analyzed the kinematic track of each limb, deduced the radar echo of human walking and gave the resolution expression. Then, the paper extracted the micro-Doppler feature of walking human radar echo by applying time-frequency analysis means, studied the relationship between human motion parameter and micro-Doppler feature, and especially studied the micro-Doppler feature of key paces of human walking.
As for extraction of human walking feature, the paper deeply studied the methods of feature parameter extraction and human pace parameter estimation raised by P. van Dorp, and applied them in field-measured data and thus extracted human micro-motion feature and estimated pace parameter; the paper also studied the inner relationship between human upper limb posture parameter and micro-Doppler feature,raised the method of extracting feature parameter from the micro-Doppler feature of the upper limbs of walking human and applied it to estimate upper limb posture parameter; then the paper raised the method and approach of estimating the posture parameter of lower limbs of walking human based on function approximation theory.
As for human motion identification, the paper raised the distinguishing method based on micro-Doppler feature analysis and pace parameter estimation. The author firstly listed the time and space features of human running and compared them with those of normal human walking. Then, based on analysis of human micro-Doppler features during walking and during running, the paper raised the features that can be used in motion identification; based on analysis and experiment of plenty of field-measured data, the paper raised a human motion distinguishing method that applies the support vector machine as classifier. The paper also deeply studied the time-frequency chart analysis method for human walking raised by Michael Otero, raised a method for distinguishing single human walking and more-than-one-person walking, and explored the method of distinguishing human beings and animals.
Based on the study on the basis of a great amount of field-measured data, the paper introduced the establishment of radar measurement system and the analysis of experiment result. Firstly, the author analyzed the design requirement of radar measurement system, designed the composition structure of radar system, and stressed the hardware design and realization of radar echo collecting system; then the author raised the experiment plan of human pace radar measurement experiment and collected plenty of experiment data. The author also listed the problems that exist in the system and raised the improvement target in future research.
At last, the author summarized the developing trend and application prospect of the dissertation study and pointed out the problems that need further study and resolution.
引文
[1] Little J J, Boyd J E. Recognizing people by their gait: the shape of motion.[J]. Journal of Computer Vision Research. 1998, 1(2): 1-32
[2] Niyogi S A, Adelson E H. Analyzing and recognizing walking figures in XYT.[J]. IEEE Proceedings on Computer Vision and Pattern Recognition. 1994: 469-474.
[3] Lee L, Grimson W E L. Gait analysis for recognition and classification.[C]. Proceedings of the 5th IEEE International Conference on Automatic Face and Gesture Recognition, 2002. 148-155
[4] Nixon M S, Carter J N. Advances in automatic gait recognition.[J]. Proceedings of the 6th IEEE International Conference on Automatic Face and Gesture Recognition. 2004: 139-144.
[5] Sabatini A M, Colla V. A method for sonar based recognition of walking people[J]. Robotics and Autonomous Systems. 1998, 24: 117-126.
[6] Weir R F, Childress D S. A new method of characterizing gait using a potable,real-time, ultrasound ranging device.[C]. IEEE,Engineering in Medicine and Biology Society: Proceedings of the 19th International Conference, 1997. 1810-1812
[7] Chen V C. Analysis of radar micro-Doppler signature with time-frequency transform.[C]. Statistical Signal and Array Processing: Proceedings of the 10th IEEE Workshop, 2000. 463-466
[8] Geisheimer J L, Marshall W S, Greneker E. A continuous-Wave(CW) Radar for Gait Analysis[C]. Proceedings of the 35th IEEE Asilomar Conference on Signal, Systems and Computers, 2001. 834-838
[9] Geisheimer J L, Greneker E, Marshall W S. A high-resolution Doppler model of human gait[C]. Proceedings of SPIE on Radar Technology, 2002. 8-18
[10] Thayaparan T, Abrol S, Riseborough E, et al. Analysis of radar micro-Doppler signatures from experimental helicopter and human data[J]. IET Radar Sonar Navig. 2007, 1(4):289-299
[11] 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
[12] van Dorp P, Groen F C A. Human walking estimation with radar[J]. IEE Proc.Radar Sonar Navig. 2003, 150(5): 356-365.
[13] van Dorp P, Groen F C A. Feature-based human motion parameter estimation with radar[J]. IET Radar Sonar Navig. 2008, 2(2): 135-145.
[14] Lin A, Bsee, Msee. A Low-Complexity Radar for Human Tracking[D]. The University of Texas at Austin, 2006.
[15] Ram S S, Li Y, Lin A, et al. Doppler-based detection and tracking of humans in indoor environments[J]. Journal of the Franklin Institute. 2008: 679-699.
[16] 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. 240-249
[17] Chen V C, Li F. Analysis of micro-Doppler signatures[J]. IEE Proceedings on Radar, Sonar and Navigation. 2003, 150(4): 271-276.
[18] 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.
[19] 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. 141-146
[20] 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.
[21]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.
[22]庄钊文,刘永祥,黎湘.目标微动特性研究进展[J].电子学报. 2007, 35(3): 520-525.
[23] Ling H. Exploitation of microdoppler and multiple scattering phenomena for radar target recognition[R]. Austin,USA: A375771, AD, The University of Texas at Austin, 2004.
[24] Stove A G, Sykes S R. A Doppler-based automatic target classifier for a battlefield surveillance radar[C]. Edinburgh, UK: Proceedings of IEEE International Conference on Radar, 2002. 419-423
[25] Williams W J, Zalubas E J. Invariant classification of time-frequency representations: applications to Doppler radar target identification[C]. Adelaide, Australia: Proceedings of DSTO/DOD Workshop, 1997
[26] Mallat S G, Zhang Z F. Matching pursuits with time frequency dictionaries[J]. IEEE Transactions on Signal Processing. 1993, 41(12): 3397-3415.
[27] Setlur P, Amin M, Thayaparan T. Micro-Doppler signal estimation for vibrating and rotating targets[C]. Sydney, Australia: Proceedings of the Eighth International Symposium on Signal Processing and its Applications, 2005. 639-642
[28] Chen V C, Des Rosiers A P. Micro-Doppler phenomenon and radar signature[C]. Adelaide, Australia: Proceedings of IEEE International Conference on Radar, 2003. 198-202
[29] Lei J J, Lu C. Target classification based on micro-Doppler signatures[C]. Washington, USA: Proceedings of IEEE International Conference on Radar, 2005. 179-183
[30] Tan R, Bender R. Analysis of Doppler measurements of people[C]. Orlando, USA: Proceedings of SPIE on Targets and Backgrounds XII: Characterization and Representation, 2006. 1-9
[31] Sutler P, Ahmad F, Amin M. Analysis of micro-Doppler signals using linear FM basis decomposition[C]. Orlando, FL: Proceedings of the SPIE Symposium on Defense and Security, Radar Sensor Technology X. 2006
[32] Hertel F, Feiden W, Bettag M. The value of micro-Doppler in stereotactic brain biopsy[J]. Minim Invasive Neurosurg. 2005, 48(3): 165-168.
[33] Zhang Y M, Amin M G. Joint Doppler and polarization characterization of moving targets[C]. Monterey, CA, USA: IEEE Antennas and Propagation Society Symposium, 2004. 3083-3086
[34] Sparr T. Moving target motion estimation and focusing in SAR images[C]. Washington, USA: Proceedings of IEEE International Conference on Radar, 2005. 290-294
[35] Silverstein S D, Hawkins Iii C E. Synthetic aperture radar image signature of rotating objects[C]. Pacific Grove, CA: Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004. 1663-1667
[36] Thayaparan T, Abrol S. Extraction of micro-Doppler from experimental SARdata[C]. Berlin, Germany: Proceedings of the International Radar Symposium, 2005
[37] Cai C J, Liu W X, Fu J S. Empirical mode decomposition of micro-Doppler signature[C]. Washington, USA: Proceedings of IEEE International Conference on Radar, 2005. 895-899
[38] Lei J J. Pattern recognition based on time-frequency distributions of radar micro-Doppler dynamics[C]. Towson, Maryland, USA: Proceedings of The Sixth International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing and First ACIS International Workshop on Self-Assembling Wireless Networks, 2005. 14-18
[39] Rajan B, Ling H. A fast algorithm for simulating doppler spectra of targets with rotating parts using the shooting and bouncing ray technique[J]. IEEE Transactions on antennas and propagation. 1998, 46(9): 1389-1391.
[40] Li J, Ling H. Application of adaptive chirplet representation for ISAR feature extraction from targets with rotating parts[J]. IEE Proceedings on Radar, Sonar and Navigation. 2003, 150(4): 284-291.
[41] Thayaparan T, Abrol S, Riseborough E. Micro-Doppler radar signatures for intelligent target recognition[R]. technical memorandum DRDC Ottawa: TM 2004-170, 2004.
[42] Chen V C. Advanced SAR imaging and feature analysis[C]. Adelaide, Australia: Proceedings of IEEE International Conference on Radar, 2003. 22-29
[43] Lawrence S, Marple J. Sharpening and bandwidth extrapolation techniques for radar micro-Doppler feature extraction[C]. Adelaide, Australia: Proceedings of IEEE International Conference on Radar, 2003. 166-170
[44] Greneker E F, Sylveste V B. Use of the envelope detection method to detect micro-Doppler[C]. Orlando, FL, USA: Proceedings of the SPIE on Passive Millimeter-Wave Imaging Technology VI and Radar Sensor Technology VII, 2003. 167-174
[45] Chen V C, Ling H. Time-Frequency Transforms for Radar Imaging and Signal Analysis[M]. Boston: Artech House, 2002: 93-104.
[46] Chen V C. Time-frequency analysis for radar imaging, target detection, and feature extraction[R]. 2004 IEEE Radar Conference -Workshop 2.3, 2004.
[47] Otaguro W, Hayes C. Microdoppler Radar system[C]. Orlando, UAS:Proceedings of SPIE on Imaging Technology and Telescopes, 2000. 268-277
[48]高红卫,文树梁.微多普勒理论建模与仿真研究[J].中国电子科学研究院学报. 2008, 3(1): 34-39.
[49]陈行勇,刘永祥,黎湘等.微多普勒分析和参数估计[J].红外与毫米波学报. 2006, 25(5): 360-363.
[50]陈行勇,黎湘,郭桂蓉等.微进动弹道导弹目标雷达特征提取[J].电子与信息学报,. 2006, 28(4): 643-646.
[51]陈行勇,黎湘,郭桂蓉等.基于旋翼微动雷达特征的空中目标识别[J].系统工程与电子技术. 2006, 28(3): 372-375.
[52]张贤达.现代信号处理(第二版)[M].清华大学出版社, 2002.
[53] 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.
[54]倪安胜.伤员探测中生命体识别技术研究[D].中国西安:第四军医大学硕士学位论文, 2003.
[55]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.
[56]陶成玉,张云卫.微波对人体的生物学作用及其防护[J].职业与健康. 2000, 16(7): 8-9.
[57] Sullivan D M, Borup D T, Gandhi O P. Use of the Finite-Difference Time-Domain Method in Calculating EM Absorption in Human Tissues[J]. IEEE Transactions on Biomedical Engineering. 1987, 34(2): 148-157.
[58] Sullivan F O, Eary J, Roy S, et al. An examination of the statistical reliability and prognostic potential of a measure of 3D spatial Heterogeneity Developed for Volumetric PET Images of Human Sarcomas[J]. IEEE Nuclear Science Symposium Conference Record, 2002. 2: 1131-1134
[59] Chen K M, Huang Y, Zhang J P. Microwave life detection systems for searching human subjects under earthquake rubble or behind barrier[J]. IEEE Trans on Biomedical Engineering. 2000, 27(1): 105-114.
[60] Chen K M, Misra D, Wang H, et al. An X-Band Microwave Life-Detection System[J]. IEEE transactions on biomedical engineering. 1986, 33(7): 697-701.
[61] Chen K M, Chuang H R. Measurement of heart and breathing signals of human subject through barriers with microwave life-detection system[C]. IEEE engineeringin medicine & biology society 10TH annual international conference : 1279-1280
[62] Chuang H R, Chen Y F, Chen K M. Microprocessor-controlled automatic clutter-cancellation circuits for microwave systems to sense physiological movements[C]. 7th IEEE Instrumentation and Measurement Technology Conference, 1990. 177-181
[63] Chuang H R, Chen Y F, Chen K M. Automatic Clutter-Canceler for Microwave Life-Detection Systems[J]. IEEE transactions on instrumentation and measurement. 1991, 40(4): 747-750.
[64]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.
[65]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.
[66]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): 179-183.
[67]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.
[68]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.
[69] Chen V C. Spatial and Temporal Independent Component Analysis of Micro-Doppler Features[R]. U.S. Government work not protected by U.S. copyright.
[70] Dogaru T, Nguyen L. FDTD Models of Electromagnetic Scattering by the Human Body[R]. US Army Research Laboratory, U.S. Government work not protected by U.S. copyright.
[71] 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.
[72] Hewish M. The last line of defense, reducing the vulnerability of[J]. Janes’s Int. Def. Rev. 1999, 10: 28-35.
[73] Nebabin V G. Methods and techniques of radar recognition[R]. ArtechHouse, 1995.
[74] Rohling H, Folster F, Kruse F. Target classification based on a GHz radarnetwork[C]. Radar 2004, Int. Conf. on Radar Systems, 2004
[75] Cutting J, Kozlowski L. Recognizing friends by their walk: Gait perception without familiarity cues.[J]. Bulletin of the Psychonomic Society. 1977, 9: 353-356.
[76] Chen V C. Doppler signatures of radar backscattering from objects with micro-motions[J]. IET Signal Process. 2008, 2(3): 291-300.
[77] Lin A, Ling H. Frontal imaging of human using three element Doppler and direction-of-arrival radar[J]. electronics letters. 2006, 42(11): 660-661
[78] Lin A, Ling H. Two-Dimensional Human Tracking Using a Three-Element Doppler and Direction-of-Arrival (DDOA) Radar[C]. IEEE Conference on Radar, 2006. 248-251
[79] Ram S S, Ling H. Simulation of Human MicroDopplers Using Computer Animation Data[C]. IEEE Conference on Radar , 2008
[80] Boulic R, Magnenat-thalmann N, Thalmann D. A global human walking model with real-time kinematic personification[J]. The Visual Computer. 1990: 344-358.
[81] Lai C P, Ruan Q, Narayanan R M. Hilbert-Huang Transform (HHT) Processing of Through-Wall Noise Radar Data for Human Activity Characterization[C]. IEEE Workshop on Signal Processing Applications for Public Security and Forensics, 2007. 1-6
[82] Hersey R K, Melvin W L, Culpepper E. Dismount Modeling and Detection from Small Aperture Moving Radar Platforms[C]. IEEE Conference on Radar, 2008. 108-113
[83] Smith G E, Woodbridge K, Baker C J. Multistatic Micro-Doppler Signature Of Personnel[C]. IEEE Conference on Radar , 2008
[84] 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
[85] Shen C N, Waeber B, Girata L. Project Radiant Outlaw[C]. San Diego;CA;USA: Proceedings of SPIE on Airborne Reconnaissance XVIII, 1994. 63-74
[86] Lovett A, Shen C N. Radiant Outlaw technology for non-cooperative identification[C]. Proceedings of TECOM Test Technology Symposium , 1997
[87] Zhang Z N, Pouliquen P, Waxman A, et al. Acoustic Micro-Doppler Gait Signatures of Humans and Animals[C]. Conference on Information Sciences andSystems, 2007, 627-630.
[88] Zhang Z N, Andreou A G. Human Identification Experiments Using Acoustic[C]. Proceedings of the Argentine School of Micro-Nanoelectronics, Technology and Applications, 2008. 81-86
[89]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.
[90]张春林.高等机构学[M].北京:北京理工大学, 1997.
[91]郭巧.现在机器人学[M].北京:北京理工大学, 1997.
[92] Bartlett R. Sports Biomechanics :Reducing Injury and Improving Performance[M]. UK: E&FN Spon, 1999.
[93]范毅方,岑人经,袁支润.采用40个自由度十五刚体人体模型模拟运动动作[J].济南大学学报(自然科学版). 2000, 21(1): 32-36.
[94] Li X F, Zhang G X, Xiao S J. Simulating Rhythmic Movement of Human Elbow Joint Using Neural Network Predictive Model[J]. Transactions of Tianjin University. 2001, 7(1).
[95]张文增,赵冬斌,陈强等.基于模型的人体运动参数检测[J].生物医学工程学杂志. 2005, 22(1): 147-150.
[96]李振波,李华.基于运动生物力学的三维人体运动模型[J].系统仿真学报. 2006, 18(10): 2992-2994.
[97]高文杰,张建国.人体上肢仿生机构运动模型的研究[J].天津轻工业学院学报. 2001: 35-39.
[98]刘卉,高云峰.人体上肢运动的Kane动力学模型[J].力学与实践. 2005, 27: 63-66.
[99]洪涛,王申康.人体正面运动的尺度骨架模型初始化算法研究[J].浙江大学学报(工学版). 2004, 38(12): 1585-1605.
[100]毕思文.数字人体数学模型[J].中国医学影像技术. 2003, 19(204): 46-51.
[101]袁泉,徐超.用于人机系统运动仿真的人体模型[J].机械设计与制造. 2001: 19-20.
[102]刘学深.人体上肢运动测量及运动模型的建立[D].天津:天津轻工业学院硕士学位论文, 1999.
[103]熊兵.人体下肢运动学和动力学的研究[D].天津:天津轻工业学院硕士学位论文, 1999.
[104]罗冠.虚拟人的运动生成及控制技术研究[D].西北工业大学博士学位论文, 2003.
[105] Molet T, Boulic R, Rezzonico S, et al. An Architecture for Immersive Evaluation of Complex Human Tasks[J]. 1999, 15(3): 475-485.
[106] Boulic R, Noser H, Thalmann D. Automatic derivation of curved human walking trajectories from synthetic vision[J]. Proceedings of Computer Animation, 1994: 93-103
[107] Peters C, O'sullivan C. Bottom-up visual attention for virtual human animation[C]. Proceedings of the 16th International Conference on CASA, 2003. 111-117
[108] Rodriguez I, Peinado M, Boulic R, et al. Bringing the human arm reachable space to a virtual environment for its analysis[J]. IEEE Proceedings 2003 International Conference on Multimedia and Expo, 2003.1: 229-232.
[109] Boulic R, Mas-sanso R, Thalmann D. Complex Character Positioning Based on a Compatible Flow Model of Multiple Supports[J]. IEEE Transactions on Visualization and Computer Graphics. 1997, 3(3): 245-261
[110] Maciel A, Boulic R, Thalmann D. Efficient Collision Detection within Deforming Spherical Sliding Contact[J]. IEEE Transactions on Visualization and Computer Graphics. 2007, 13(3): 518-529.
[111] Brailean J C, Sullivan B J, Tu C, et al. Evaluating the EM algorithm for image processing using a human visual fidelity criterion[C]. IEEE International Conference on Acoustics, Speech, and Signal Processing, 1991. 4. 2957-2960
[112] Aubel A, Boulic R, Thalmann D. Real-Time Display of Virtual Humans Levels of Details and Impostors[J]. IEEE Transactions on Circuits and Systems for Video Technology. 2000, 10(2): 207-217
[113] Thalmann D, Farenc N, Boulic R. Virtual human life simulation and database: why and how[C]. IEEE Proceedings 1999 International Symposium on Database Applications in Non-Traditional Environments,1999. 471-479
[114] Rodriguez, Boulic R, Meziat D. Visualizing Human Fatigue at Joint Level with the Half-joint Pair Concept[C]. Proceedings of SPIE-IS&T Electronic Imaging, SPIE, 2003. 37-45
[115]汪丽.面向动作分析的虚拟人体建模研究[D].山东大学硕士学位论文, 2006.
[116]张献宝.人机工程设计的虚拟现实人开发与应用研究[D].西北工业大学硕士学位论文, 1999.
[117]刘艳.三维虚拟人行为控制关键技术的研究[D].天津:天津大学博士学位论文, 2003.
[118]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.
[119]徐晖.虚拟人物运动仿真研究[D].西安:西安交通大学博士学位论文, 1999.
[120]贺怀清.虚拟人的建模及运动控制算法的研究[D].哈尔滨:哈尔滨工业大学博士学位论文, 2001.
[121]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.
[122]窦瑞军.类人型机器人稳定步态设计及动态步行研究[D].上海交通大学博士学位论文, 2002.
[123]柯显信.仿人形机器人双足动态步行研究[D].上海大学博士学位论文, 2005.
[124]王淑艳.仿人型跑步机器人的稳定性条件及步态规划[D].西安:西安电子科技大学硕士学位论文, 2006.
[125]周云龙.双足机器人的模型与控制方法研究[D].东北大学博士学位论文, 2004.
[126]刘英卓.拟人形机器人建模、控制与协调研究[D].中国科学院沈阳自动化研究所博士学位论文, 2003.
[127]张永学.双足机器人步态规划及步行控制研究[D].哈尔滨:哈尔滨工业大学博士学位论文, 2001.
[128]陆根源,陈孝桢.信号检测与参数估计[M].北京:科学出版社, 2004.
[129]梁红,胡旭娟,朱云周.基于RSPWVD-Hough的多分量LFM信号检测[J].系统仿真学报. 2007, 19(13): 3030-3032.
[130]张志涌等.精通MATLAB6.5版教程[M].北京:北京航空航天大学出版社, 2003.
[131] Hansen K V, Toft P A. Fast curve estimation using preconditioned generalizedradon transform[J]. IEEE Trans on Image Process. 1996, 5(12): 1651-1661.
[132]贺治华.机载毫米波雷达目标识别关键技术研究[D].中国长沙:国防科技大学博士学位论文, 2005.
[133] Yam C Y, Nixon M S, Carter J N. On the relationship of human walking and running:Automatic Person Idendification by Gait[C]. IEEE Proceedings 16th International Conference on Pattern Recognition, 2002. 1. 287-290
[134] Yam C Y, Nixon M S, Carter J N. Performance analysis on new biometric gait motion model[C]. Fifth IEEE Southwest Symposium on Image Analysis and Interpretation, IEEE, 2002. 31-34
[135] Wu Y, Yu T. A Field Model for Human Detection and Tracking[J]. IEEE Transactions on pattern analysis and machine intelligence. 2006, 28(5): 753-765.
[136]魏航信.仿人跑步机器人快速跑步研究[D].西安:西安电子科技大学博士学位论文, 2006.
[137]杜晓东,李岐强.支持向量机及其算法研究[J].信号处理与模式识别. 2005(3): 37-40.
[2] Niyogi S A, Adelson E H. Analyzing and recognizing walking figures in XYT.[J]. IEEE Proceedings on Computer Vision and Pattern Recognition. 1994: 469-474.
[3] Lee L, Grimson W E L. Gait analysis for recognition and classification.[C]. Proceedings of the 5th IEEE International Conference on Automatic Face and Gesture Recognition, 2002. 148-155
[4] Nixon M S, Carter J N. Advances in automatic gait recognition.[J]. Proceedings of the 6th IEEE International Conference on Automatic Face and Gesture Recognition. 2004: 139-144.
[5] Sabatini A M, Colla V. A method for sonar based recognition of walking people[J]. Robotics and Autonomous Systems. 1998, 24: 117-126.
[6] Weir R F, Childress D S. A new method of characterizing gait using a potable,real-time, ultrasound ranging device.[C]. IEEE,Engineering in Medicine and Biology Society: Proceedings of the 19th International Conference, 1997. 1810-1812
[7] Chen V C. Analysis of radar micro-Doppler signature with time-frequency transform.[C]. Statistical Signal and Array Processing: Proceedings of the 10th IEEE Workshop, 2000. 463-466
[8] Geisheimer J L, Marshall W S, Greneker E. A continuous-Wave(CW) Radar for Gait Analysis[C]. Proceedings of the 35th IEEE Asilomar Conference on Signal, Systems and Computers, 2001. 834-838
[9] Geisheimer J L, Greneker E, Marshall W S. A high-resolution Doppler model of human gait[C]. Proceedings of SPIE on Radar Technology, 2002. 8-18
[10] Thayaparan T, Abrol S, Riseborough E, et al. Analysis of radar micro-Doppler signatures from experimental helicopter and human data[J]. IET Radar Sonar Navig. 2007, 1(4):289-299
[11] 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
[12] van Dorp P, Groen F C A. Human walking estimation with radar[J]. IEE Proc.Radar Sonar Navig. 2003, 150(5): 356-365.
[13] van Dorp P, Groen F C A. Feature-based human motion parameter estimation with radar[J]. IET Radar Sonar Navig. 2008, 2(2): 135-145.
[14] Lin A, Bsee, Msee. A Low-Complexity Radar for Human Tracking[D]. The University of Texas at Austin, 2006.
[15] Ram S S, Li Y, Lin A, et al. Doppler-based detection and tracking of humans in indoor environments[J]. Journal of the Franklin Institute. 2008: 679-699.
[16] 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. 240-249
[17] Chen V C, Li F. Analysis of micro-Doppler signatures[J]. IEE Proceedings on Radar, Sonar and Navigation. 2003, 150(4): 271-276.
[18] 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.
[19] 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. 141-146
[20] 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.
[21]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.
[22]庄钊文,刘永祥,黎湘.目标微动特性研究进展[J].电子学报. 2007, 35(3): 520-525.
[23] Ling H. Exploitation of microdoppler and multiple scattering phenomena for radar target recognition[R]. Austin,USA: A375771, AD, The University of Texas at Austin, 2004.
[24] Stove A G, Sykes S R. A Doppler-based automatic target classifier for a battlefield surveillance radar[C]. Edinburgh, UK: Proceedings of IEEE International Conference on Radar, 2002. 419-423
[25] Williams W J, Zalubas E J. Invariant classification of time-frequency representations: applications to Doppler radar target identification[C]. Adelaide, Australia: Proceedings of DSTO/DOD Workshop, 1997
[26] Mallat S G, Zhang Z F. Matching pursuits with time frequency dictionaries[J]. IEEE Transactions on Signal Processing. 1993, 41(12): 3397-3415.
[27] Setlur P, Amin M, Thayaparan T. Micro-Doppler signal estimation for vibrating and rotating targets[C]. Sydney, Australia: Proceedings of the Eighth International Symposium on Signal Processing and its Applications, 2005. 639-642
[28] Chen V C, Des Rosiers A P. Micro-Doppler phenomenon and radar signature[C]. Adelaide, Australia: Proceedings of IEEE International Conference on Radar, 2003. 198-202
[29] Lei J J, Lu C. Target classification based on micro-Doppler signatures[C]. Washington, USA: Proceedings of IEEE International Conference on Radar, 2005. 179-183
[30] Tan R, Bender R. Analysis of Doppler measurements of people[C]. Orlando, USA: Proceedings of SPIE on Targets and Backgrounds XII: Characterization and Representation, 2006. 1-9
[31] Sutler P, Ahmad F, Amin M. Analysis of micro-Doppler signals using linear FM basis decomposition[C]. Orlando, FL: Proceedings of the SPIE Symposium on Defense and Security, Radar Sensor Technology X. 2006
[32] Hertel F, Feiden W, Bettag M. The value of micro-Doppler in stereotactic brain biopsy[J]. Minim Invasive Neurosurg. 2005, 48(3): 165-168.
[33] Zhang Y M, Amin M G. Joint Doppler and polarization characterization of moving targets[C]. Monterey, CA, USA: IEEE Antennas and Propagation Society Symposium, 2004. 3083-3086
[34] Sparr T. Moving target motion estimation and focusing in SAR images[C]. Washington, USA: Proceedings of IEEE International Conference on Radar, 2005. 290-294
[35] Silverstein S D, Hawkins Iii C E. Synthetic aperture radar image signature of rotating objects[C]. Pacific Grove, CA: Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004. 1663-1667
[36] Thayaparan T, Abrol S. Extraction of micro-Doppler from experimental SARdata[C]. Berlin, Germany: Proceedings of the International Radar Symposium, 2005
[37] Cai C J, Liu W X, Fu J S. Empirical mode decomposition of micro-Doppler signature[C]. Washington, USA: Proceedings of IEEE International Conference on Radar, 2005. 895-899
[38] Lei J J. Pattern recognition based on time-frequency distributions of radar micro-Doppler dynamics[C]. Towson, Maryland, USA: Proceedings of The Sixth International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing and First ACIS International Workshop on Self-Assembling Wireless Networks, 2005. 14-18
[39] Rajan B, Ling H. A fast algorithm for simulating doppler spectra of targets with rotating parts using the shooting and bouncing ray technique[J]. IEEE Transactions on antennas and propagation. 1998, 46(9): 1389-1391.
[40] Li J, Ling H. Application of adaptive chirplet representation for ISAR feature extraction from targets with rotating parts[J]. IEE Proceedings on Radar, Sonar and Navigation. 2003, 150(4): 284-291.
[41] Thayaparan T, Abrol S, Riseborough E. Micro-Doppler radar signatures for intelligent target recognition[R]. technical memorandum DRDC Ottawa: TM 2004-170, 2004.
[42] Chen V C. Advanced SAR imaging and feature analysis[C]. Adelaide, Australia: Proceedings of IEEE International Conference on Radar, 2003. 22-29
[43] Lawrence S, Marple J. Sharpening and bandwidth extrapolation techniques for radar micro-Doppler feature extraction[C]. Adelaide, Australia: Proceedings of IEEE International Conference on Radar, 2003. 166-170
[44] Greneker E F, Sylveste V B. Use of the envelope detection method to detect micro-Doppler[C]. Orlando, FL, USA: Proceedings of the SPIE on Passive Millimeter-Wave Imaging Technology VI and Radar Sensor Technology VII, 2003. 167-174
[45] Chen V C, Ling H. Time-Frequency Transforms for Radar Imaging and Signal Analysis[M]. Boston: Artech House, 2002: 93-104.
[46] Chen V C. Time-frequency analysis for radar imaging, target detection, and feature extraction[R]. 2004 IEEE Radar Conference -Workshop 2.3, 2004.
[47] Otaguro W, Hayes C. Microdoppler Radar system[C]. Orlando, UAS:Proceedings of SPIE on Imaging Technology and Telescopes, 2000. 268-277
[48]高红卫,文树梁.微多普勒理论建模与仿真研究[J].中国电子科学研究院学报. 2008, 3(1): 34-39.
[49]陈行勇,刘永祥,黎湘等.微多普勒分析和参数估计[J].红外与毫米波学报. 2006, 25(5): 360-363.
[50]陈行勇,黎湘,郭桂蓉等.微进动弹道导弹目标雷达特征提取[J].电子与信息学报,. 2006, 28(4): 643-646.
[51]陈行勇,黎湘,郭桂蓉等.基于旋翼微动雷达特征的空中目标识别[J].系统工程与电子技术. 2006, 28(3): 372-375.
[52]张贤达.现代信号处理(第二版)[M].清华大学出版社, 2002.
[53] 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.
[54]倪安胜.伤员探测中生命体识别技术研究[D].中国西安:第四军医大学硕士学位论文, 2003.
[55]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.
[56]陶成玉,张云卫.微波对人体的生物学作用及其防护[J].职业与健康. 2000, 16(7): 8-9.
[57] Sullivan D M, Borup D T, Gandhi O P. Use of the Finite-Difference Time-Domain Method in Calculating EM Absorption in Human Tissues[J]. IEEE Transactions on Biomedical Engineering. 1987, 34(2): 148-157.
[58] Sullivan F O, Eary J, Roy S, et al. An examination of the statistical reliability and prognostic potential of a measure of 3D spatial Heterogeneity Developed for Volumetric PET Images of Human Sarcomas[J]. IEEE Nuclear Science Symposium Conference Record, 2002. 2: 1131-1134
[59] Chen K M, Huang Y, Zhang J P. Microwave life detection systems for searching human subjects under earthquake rubble or behind barrier[J]. IEEE Trans on Biomedical Engineering. 2000, 27(1): 105-114.
[60] Chen K M, Misra D, Wang H, et al. An X-Band Microwave Life-Detection System[J]. IEEE transactions on biomedical engineering. 1986, 33(7): 697-701.
[61] Chen K M, Chuang H R. Measurement of heart and breathing signals of human subject through barriers with microwave life-detection system[C]. IEEE engineeringin medicine & biology society 10TH annual international conference : 1279-1280
[62] Chuang H R, Chen Y F, Chen K M. Microprocessor-controlled automatic clutter-cancellation circuits for microwave systems to sense physiological movements[C]. 7th IEEE Instrumentation and Measurement Technology Conference, 1990. 177-181
[63] Chuang H R, Chen Y F, Chen K M. Automatic Clutter-Canceler for Microwave Life-Detection Systems[J]. IEEE transactions on instrumentation and measurement. 1991, 40(4): 747-750.
[64]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.
[65]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.
[66]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): 179-183.
[67]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.
[68]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.
[69] Chen V C. Spatial and Temporal Independent Component Analysis of Micro-Doppler Features[R]. U.S. Government work not protected by U.S. copyright.
[70] Dogaru T, Nguyen L. FDTD Models of Electromagnetic Scattering by the Human Body[R]. US Army Research Laboratory, U.S. Government work not protected by U.S. copyright.
[71] 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.
[72] Hewish M. The last line of defense, reducing the vulnerability of[J]. Janes’s Int. Def. Rev. 1999, 10: 28-35.
[73] Nebabin V G. Methods and techniques of radar recognition[R]. ArtechHouse, 1995.
[74] Rohling H, Folster F, Kruse F. Target classification based on a GHz radarnetwork[C]. Radar 2004, Int. Conf. on Radar Systems, 2004
[75] Cutting J, Kozlowski L. Recognizing friends by their walk: Gait perception without familiarity cues.[J]. Bulletin of the Psychonomic Society. 1977, 9: 353-356.
[76] Chen V C. Doppler signatures of radar backscattering from objects with micro-motions[J]. IET Signal Process. 2008, 2(3): 291-300.
[77] Lin A, Ling H. Frontal imaging of human using three element Doppler and direction-of-arrival radar[J]. electronics letters. 2006, 42(11): 660-661
[78] Lin A, Ling H. Two-Dimensional Human Tracking Using a Three-Element Doppler and Direction-of-Arrival (DDOA) Radar[C]. IEEE Conference on Radar, 2006. 248-251
[79] Ram S S, Ling H. Simulation of Human MicroDopplers Using Computer Animation Data[C]. IEEE Conference on Radar , 2008
[80] Boulic R, Magnenat-thalmann N, Thalmann D. A global human walking model with real-time kinematic personification[J]. The Visual Computer. 1990: 344-358.
[81] Lai C P, Ruan Q, Narayanan R M. Hilbert-Huang Transform (HHT) Processing of Through-Wall Noise Radar Data for Human Activity Characterization[C]. IEEE Workshop on Signal Processing Applications for Public Security and Forensics, 2007. 1-6
[82] Hersey R K, Melvin W L, Culpepper E. Dismount Modeling and Detection from Small Aperture Moving Radar Platforms[C]. IEEE Conference on Radar, 2008. 108-113
[83] Smith G E, Woodbridge K, Baker C J. Multistatic Micro-Doppler Signature Of Personnel[C]. IEEE Conference on Radar , 2008
[84] 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
[85] Shen C N, Waeber B, Girata L. Project Radiant Outlaw[C]. San Diego;CA;USA: Proceedings of SPIE on Airborne Reconnaissance XVIII, 1994. 63-74
[86] Lovett A, Shen C N. Radiant Outlaw technology for non-cooperative identification[C]. Proceedings of TECOM Test Technology Symposium , 1997
[87] Zhang Z N, Pouliquen P, Waxman A, et al. Acoustic Micro-Doppler Gait Signatures of Humans and Animals[C]. Conference on Information Sciences andSystems, 2007, 627-630.
[88] Zhang Z N, Andreou A G. Human Identification Experiments Using Acoustic[C]. Proceedings of the Argentine School of Micro-Nanoelectronics, Technology and Applications, 2008. 81-86
[89]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.
[90]张春林.高等机构学[M].北京:北京理工大学, 1997.
[91]郭巧.现在机器人学[M].北京:北京理工大学, 1997.
[92] Bartlett R. Sports Biomechanics :Reducing Injury and Improving Performance[M]. UK: E&FN Spon, 1999.
[93]范毅方,岑人经,袁支润.采用40个自由度十五刚体人体模型模拟运动动作[J].济南大学学报(自然科学版). 2000, 21(1): 32-36.
[94] Li X F, Zhang G X, Xiao S J. Simulating Rhythmic Movement of Human Elbow Joint Using Neural Network Predictive Model[J]. Transactions of Tianjin University. 2001, 7(1).
[95]张文增,赵冬斌,陈强等.基于模型的人体运动参数检测[J].生物医学工程学杂志. 2005, 22(1): 147-150.
[96]李振波,李华.基于运动生物力学的三维人体运动模型[J].系统仿真学报. 2006, 18(10): 2992-2994.
[97]高文杰,张建国.人体上肢仿生机构运动模型的研究[J].天津轻工业学院学报. 2001: 35-39.
[98]刘卉,高云峰.人体上肢运动的Kane动力学模型[J].力学与实践. 2005, 27: 63-66.
[99]洪涛,王申康.人体正面运动的尺度骨架模型初始化算法研究[J].浙江大学学报(工学版). 2004, 38(12): 1585-1605.
[100]毕思文.数字人体数学模型[J].中国医学影像技术. 2003, 19(204): 46-51.
[101]袁泉,徐超.用于人机系统运动仿真的人体模型[J].机械设计与制造. 2001: 19-20.
[102]刘学深.人体上肢运动测量及运动模型的建立[D].天津:天津轻工业学院硕士学位论文, 1999.
[103]熊兵.人体下肢运动学和动力学的研究[D].天津:天津轻工业学院硕士学位论文, 1999.
[104]罗冠.虚拟人的运动生成及控制技术研究[D].西北工业大学博士学位论文, 2003.
[105] Molet T, Boulic R, Rezzonico S, et al. An Architecture for Immersive Evaluation of Complex Human Tasks[J]. 1999, 15(3): 475-485.
[106] Boulic R, Noser H, Thalmann D. Automatic derivation of curved human walking trajectories from synthetic vision[J]. Proceedings of Computer Animation, 1994: 93-103
[107] Peters C, O'sullivan C. Bottom-up visual attention for virtual human animation[C]. Proceedings of the 16th International Conference on CASA, 2003. 111-117
[108] Rodriguez I, Peinado M, Boulic R, et al. Bringing the human arm reachable space to a virtual environment for its analysis[J]. IEEE Proceedings 2003 International Conference on Multimedia and Expo, 2003.1: 229-232.
[109] Boulic R, Mas-sanso R, Thalmann D. Complex Character Positioning Based on a Compatible Flow Model of Multiple Supports[J]. IEEE Transactions on Visualization and Computer Graphics. 1997, 3(3): 245-261
[110] Maciel A, Boulic R, Thalmann D. Efficient Collision Detection within Deforming Spherical Sliding Contact[J]. IEEE Transactions on Visualization and Computer Graphics. 2007, 13(3): 518-529.
[111] Brailean J C, Sullivan B J, Tu C, et al. Evaluating the EM algorithm for image processing using a human visual fidelity criterion[C]. IEEE International Conference on Acoustics, Speech, and Signal Processing, 1991. 4. 2957-2960
[112] Aubel A, Boulic R, Thalmann D. Real-Time Display of Virtual Humans Levels of Details and Impostors[J]. IEEE Transactions on Circuits and Systems for Video Technology. 2000, 10(2): 207-217
[113] Thalmann D, Farenc N, Boulic R. Virtual human life simulation and database: why and how[C]. IEEE Proceedings 1999 International Symposium on Database Applications in Non-Traditional Environments,1999. 471-479
[114] Rodriguez, Boulic R, Meziat D. Visualizing Human Fatigue at Joint Level with the Half-joint Pair Concept[C]. Proceedings of SPIE-IS&T Electronic Imaging, SPIE, 2003. 37-45
[115]汪丽.面向动作分析的虚拟人体建模研究[D].山东大学硕士学位论文, 2006.
[116]张献宝.人机工程设计的虚拟现实人开发与应用研究[D].西北工业大学硕士学位论文, 1999.
[117]刘艳.三维虚拟人行为控制关键技术的研究[D].天津:天津大学博士学位论文, 2003.
[118]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.
[119]徐晖.虚拟人物运动仿真研究[D].西安:西安交通大学博士学位论文, 1999.
[120]贺怀清.虚拟人的建模及运动控制算法的研究[D].哈尔滨:哈尔滨工业大学博士学位论文, 2001.
[121]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.
[122]窦瑞军.类人型机器人稳定步态设计及动态步行研究[D].上海交通大学博士学位论文, 2002.
[123]柯显信.仿人形机器人双足动态步行研究[D].上海大学博士学位论文, 2005.
[124]王淑艳.仿人型跑步机器人的稳定性条件及步态规划[D].西安:西安电子科技大学硕士学位论文, 2006.
[125]周云龙.双足机器人的模型与控制方法研究[D].东北大学博士学位论文, 2004.
[126]刘英卓.拟人形机器人建模、控制与协调研究[D].中国科学院沈阳自动化研究所博士学位论文, 2003.
[127]张永学.双足机器人步态规划及步行控制研究[D].哈尔滨:哈尔滨工业大学博士学位论文, 2001.
[128]陆根源,陈孝桢.信号检测与参数估计[M].北京:科学出版社, 2004.
[129]梁红,胡旭娟,朱云周.基于RSPWVD-Hough的多分量LFM信号检测[J].系统仿真学报. 2007, 19(13): 3030-3032.
[130]张志涌等.精通MATLAB6.5版教程[M].北京:北京航空航天大学出版社, 2003.
[131] Hansen K V, Toft P A. Fast curve estimation using preconditioned generalizedradon transform[J]. IEEE Trans on Image Process. 1996, 5(12): 1651-1661.
[132]贺治华.机载毫米波雷达目标识别关键技术研究[D].中国长沙:国防科技大学博士学位论文, 2005.
[133] Yam C Y, Nixon M S, Carter J N. On the relationship of human walking and running:Automatic Person Idendification by Gait[C]. IEEE Proceedings 16th International Conference on Pattern Recognition, 2002. 1. 287-290
[134] Yam C Y, Nixon M S, Carter J N. Performance analysis on new biometric gait motion model[C]. Fifth IEEE Southwest Symposium on Image Analysis and Interpretation, IEEE, 2002. 31-34
[135] Wu Y, Yu T. A Field Model for Human Detection and Tracking[J]. IEEE Transactions on pattern analysis and machine intelligence. 2006, 28(5): 753-765.
[136]魏航信.仿人跑步机器人快速跑步研究[D].西安:西安电子科技大学博士学位论文, 2006.
[137]杜晓东,李岐强.支持向量机及其算法研究[J].信号处理与模式识别. 2005(3): 37-40.