微动目标的运动参数估计和识别方法研究
|
摘要
利用雷达目标微动特性进行目标检测和识别近年来受到雷达界广泛的关注。一般把雷达目标除质心平动以外的小幅振动、转动和其它高阶运动统称为微动,微动引起的雷达可观测量微多普勒特征包含了目标的运动、尺寸、形状等大量信息。因此,微动特征和微多普勒特征作为有效的雷达识别特征,为目标识别提供方法和思路。
本文研究了微动目标的运动参数估计方法和微动目标的雷达特征提取技术,论文首先对国内外微动目标雷达特征分析与提取的研究现状、论文的研究背景、本文主要工作进行了详细的阐述。
论文首先介绍了微动以及微多普勒的概念,分析了微动对目标回波的调制作用和微多普勒的数学原理。在散射中心模型下,建立了弹头微动的运动模型,推导了进动状态下,进动目标回波和微多普勒的数学表达式,研究了单个散射点下微动特征的提取和微动目标运动参数估计的方法。
论文从时频分析技术方面研究了微动目标的雷达特征提取和参数估计的方法。研究了导弹目标进动状态下其短时傅里叶变换的数学表达式,提出了估计多散射点的瞬时多普勒线性和的方法,对估计的各散射点微多普勒线性和做傅里叶谱分析,可估计弹头进动时的各个运动参数。并提出傅里叶谱的波形熵特征,有效地区分进动弹头和自旋诱饵。
论文研究了微动目标的傅里叶谱,从理论上推导了弹头在微动状态下的傅里叶谱的数学表达式,得到了进动状态下傅里叶谱谱峰出现的位置,从而得到不同微动状态下的傅里叶谱特征,提供一种用于区分复杂运动如进动和简单运动如自旋或摆动的方法。并研究了利用傅里叶谱和倒谱估计微动目标运动参数的方法。
论文还研究了从进动目标的回波中,直接提取进动目标的运动参数的方法。
最后,对论文工作和研究方向进行了总结,指出了需要进一步研究和解决的问题。
Using target micro-motion characteristics for target detection and recognition is a hot topic in radar community recently. Micro-motion is commonly referred to small mechanical vibrations or rotations in addition to mass translation which may induce additional frequency modulation on the received target echoed signal, called micro-Doppler effect. Micro-Doppler signatures enable some properties of the target to be determined such as motion condition, size, shape, et al. Therefore, using micro-motion signature and micro-Doppler signature as radar features to identify targets of interest is proven to be an effective way.
This paper investigates methods for motion parameter estimation from and radar signature extraction from targets with micro-motions. Brief reviews and comments of the research background, present situation, and the main contributions of this paper are introduced at the very beginning.
Firstly, this paper introduces the basic conceptions of micro-motion and micro-Doppler, examines the modulation to the target echoes induced by micro-motion as well as mathematics and computation technique involved in micro-motion or micro-Doppler. This paper establishes a motion model for warhead with micro-motion, derives the mathematic expression for returned echo and the micro-Doppler of the target of interest, and studies the method for motion parameter estimation and signature extraction.
Time-frequency transform is used to analyze micro-Doppler signal due to its time-varying property for target feature extraction. The short-time Fourier Transform (STFT) mathematic expression for echoes from target with micro-motion is derived. Based on this expression a method for estimating the linear sum of micro-Doppler for multi-scatters is proposed. Then parameter extraction can be done by applying the Fourier Transform to the linear sum. Then waveform entropy can be used as an effective characteristic to recognize the warhead from decoys.
This paper also investigates the Fourier spectrum of the target with different micro-motion. The positions where the spectrum peaks locate are estimated in a mathematic way. Then features are extracted for identifying warhead from decoys based on their difference in micro-motion. This paper also investigates the application of Fourier spectrum and cepstrum in the parameter estimation for target with micro-motion.
In addition to the spectrum application, the paper also makes efforts on methods for parameter estimation from other aspects.
This paper is concluded with a summary and a list of some significant and valuable problems as a reference in further research.
本文研究了微动目标的运动参数估计方法和微动目标的雷达特征提取技术,论文首先对国内外微动目标雷达特征分析与提取的研究现状、论文的研究背景、本文主要工作进行了详细的阐述。
论文首先介绍了微动以及微多普勒的概念,分析了微动对目标回波的调制作用和微多普勒的数学原理。在散射中心模型下,建立了弹头微动的运动模型,推导了进动状态下,进动目标回波和微多普勒的数学表达式,研究了单个散射点下微动特征的提取和微动目标运动参数估计的方法。
论文从时频分析技术方面研究了微动目标的雷达特征提取和参数估计的方法。研究了导弹目标进动状态下其短时傅里叶变换的数学表达式,提出了估计多散射点的瞬时多普勒线性和的方法,对估计的各散射点微多普勒线性和做傅里叶谱分析,可估计弹头进动时的各个运动参数。并提出傅里叶谱的波形熵特征,有效地区分进动弹头和自旋诱饵。
论文研究了微动目标的傅里叶谱,从理论上推导了弹头在微动状态下的傅里叶谱的数学表达式,得到了进动状态下傅里叶谱谱峰出现的位置,从而得到不同微动状态下的傅里叶谱特征,提供一种用于区分复杂运动如进动和简单运动如自旋或摆动的方法。并研究了利用傅里叶谱和倒谱估计微动目标运动参数的方法。
论文还研究了从进动目标的回波中,直接提取进动目标的运动参数的方法。
最后,对论文工作和研究方向进行了总结,指出了需要进一步研究和解决的问题。
Using target micro-motion characteristics for target detection and recognition is a hot topic in radar community recently. Micro-motion is commonly referred to small mechanical vibrations or rotations in addition to mass translation which may induce additional frequency modulation on the received target echoed signal, called micro-Doppler effect. Micro-Doppler signatures enable some properties of the target to be determined such as motion condition, size, shape, et al. Therefore, using micro-motion signature and micro-Doppler signature as radar features to identify targets of interest is proven to be an effective way.
This paper investigates methods for motion parameter estimation from and radar signature extraction from targets with micro-motions. Brief reviews and comments of the research background, present situation, and the main contributions of this paper are introduced at the very beginning.
Firstly, this paper introduces the basic conceptions of micro-motion and micro-Doppler, examines the modulation to the target echoes induced by micro-motion as well as mathematics and computation technique involved in micro-motion or micro-Doppler. This paper establishes a motion model for warhead with micro-motion, derives the mathematic expression for returned echo and the micro-Doppler of the target of interest, and studies the method for motion parameter estimation and signature extraction.
Time-frequency transform is used to analyze micro-Doppler signal due to its time-varying property for target feature extraction. The short-time Fourier Transform (STFT) mathematic expression for echoes from target with micro-motion is derived. Based on this expression a method for estimating the linear sum of micro-Doppler for multi-scatters is proposed. Then parameter extraction can be done by applying the Fourier Transform to the linear sum. Then waveform entropy can be used as an effective characteristic to recognize the warhead from decoys.
This paper also investigates the Fourier spectrum of the target with different micro-motion. The positions where the spectrum peaks locate are estimated in a mathematic way. Then features are extracted for identifying warhead from decoys based on their difference in micro-motion. This paper also investigates the application of Fourier spectrum and cepstrum in the parameter estimation for target with micro-motion.
In addition to the spectrum application, the paper also makes efforts on methods for parameter estimation from other aspects.
This paper is concluded with a summary and a list of some significant and valuable problems as a reference in further research.
引文
[1] V.C.Chen, F.Li, S.-S.Ho, et al. Analysis of micro-Doppler signatures[J]. IEE Proceedings on Radar,Sonar and Navigation.2003,150(4).271-276.
[2] V.C.Chen,Micro-Doppler effect of micro-motion dynamics:a review[C],Proceedings of SPIE on Independent Component Analyses,Wavelets,and Neural Networks,Orlando,USA,2003,5102.240-249.
[3] 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.
[4] Victor C. Chen. Analysis of Radar Micro-Doppler Signature With Time-Frequency Transform[J].Proc.10th IEEE Workshop on Staristical signal and array processing, Pocono Manor,PA,USA,August 2000.463-466.
[5]陈建文,李士国.基于目标运动分辨技术提取导弹目标运动特征[J].现代雷达,2003,25(6).5-8.
[6]陈行勇,黎湘,郭桂荣,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.
[7] SUN Hui-xia, LIU zheng. Micro-Doppler Feature Extraction for Ballistic Missile Warhead[C].IEEE International Conference on Information and Automation.Zhangjiajie,China,2008.1333-1336.
[8] Jiajin Lei. Pattern Recognition Based on Time-Frequency Distributions of Radar Micro-Doppler Dynamics[C].IEEE Proceedings of the Sixth International Conference on SNPD/SAWN, Washington DC, USA,2005.14-18.
[9]高红卫,谢良贵,文树梁等.弹道导弹目标为多普勒特征提取[J].雷达科学与技术,2008,6(2).96-101.
[10] Sun Zhaoqiang, Li Baozhu, Lu Yaobing. Research on Mocro-Motion and Micro-Doppler of Ballistic Targets[C]. IET International Radar Conference,Guilin,China,2009,209.
[11]陈行勇,黎湘,姜斌.基于微多普勒特征的空中目标识别[J].现代雷达,2006,28(10).30-33.
[12]张顺生,曾涛.基于keystone变换的微弱目标检测[J].电子学报.2005,33(9).1675-1678。
[13]陈文驰,保铮,邢孟道.基于Keystone变换的低信噪比ISAR成像[J].西安电子科技大学学报(自然科学版).2003,4,30(2)。
[14] Pawan Setlur and Moeness Amin.Micro-doppler signal estimation for vibrating and rotating targets[J]IEEE on Signal Processing and Its Applications 2005.639-642。
[15] T. Sato. Shape Estimation of Space Debris Using Single-Range Doppler Interferometry[J]. IEEE Trans. on GRS. Mar 1999, Vol.37(2). 1000-1005。
[16] Qun Zhang,Tat Soon Yeo,Hwee Siang Tan etc. Imaging of a Moving Target With Rotating Parts Based on the Hough Transform[J]. IEEE trans. on GRS.2008 ,Vol. 46(1).pp291-299。
[17] Q. Wang, M. Xing, G. Lu, Z. Bao. High Resolution Three-Dimensional Radar Imaging for Rapidly Spinning Targets[J]. IEEE Trans. on GRS. 2008,Vol. 46(1).pp22-31。
[18] Q. Wang,M. Xing,G. Lu, Z. Bao .SRMF-CLEAN Imaging Algorithm for Space Debris[J]. IEEE Trans. on AP. 2007, Dec .Vol.55(12). 3524-3534。
[19] Chengjie Cai, Weixian Liu, Jeffrey S. Fu,et al..Empirical Mode Decomposition of Micro-Doppler Signature[C]. Proceedings of Internaltional Conference on Radar, Washington, USA, May 2005,895—899。
[20] N. E. Huang, Z. Shen, S. R. Long, et al.The Empirical Mode Decomposition and Hilbert Spectrum for Nonlinear and Non-stationary Time Series Analysis[J]. Proc. R.Soc. London A, 1998.903-995。
[21]刘永祥,黎湘,庄钊文.文导弹防御系统中的雷达目标识别研究[J].国防科技大学学报.2004,26(4).6-9。
[22]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.2006,10,25(5).360-363。
[23] LovettA, Shen C, OtaguroW. Micro-doppler: non-cooperative target classification /identification[R]. A420040, AD,Maryland, USA: Naval Air Warfare Center Aircraft Division.2004。
[24]刘永祥,黎湘,庄钊文.空间目标进动特性及在雷达识别中的应用[J].自然科学进展.2004,1.14(11).1329-1332。
[25] Cheryl Resch,Fernando J. Pineda,and I-Jeng Wang.Automatic Recognition and Assignment of Missile Pieces in Clutter[J].IEEE,1999.3177-3181。
[26] Hongying Hu,Jing Kang,and Lina Guan.Instantaneous Frequency Estimation Based on Empirical Mode Decomposition[C].Preceedings of the 7th World Congress on Intelligent Control and Automation.2008,6.3049-3051。
[27] Yongrui Zheng, Qiuhua Lin,Fuliang Yin,et al. Speech Enhancement Using ICA with EMD-Based Reference[J].Springer-Verlag Berlin Heidelberg.ICA2006,LNCS 3889.739-746.
[28] Liang, H. L., Lin, Q. H., and Chen, J. D. Z. Application of the empirical mode decompositionto the analysis of esophageal manometric data in gastroesophageal reflux disease[J].IEEE Transactions on Biomedical Engineering. 2005, vol. 52(10). 1692–1701.
[29]陈行勇.微动目标雷达特征提取技术研究.国防科技大学博士学位论文.2006。
[30]高如云,陆曼茹,张企民,等.通信电子线路[书].西安电子科技大学出版社,第八章.2002.192-196.
[2] V.C.Chen,Micro-Doppler effect of micro-motion dynamics:a review[C],Proceedings of SPIE on Independent Component Analyses,Wavelets,and Neural Networks,Orlando,USA,2003,5102.240-249.
[3] 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.
[4] Victor C. Chen. Analysis of Radar Micro-Doppler Signature With Time-Frequency Transform[J].Proc.10th IEEE Workshop on Staristical signal and array processing, Pocono Manor,PA,USA,August 2000.463-466.
[5]陈建文,李士国.基于目标运动分辨技术提取导弹目标运动特征[J].现代雷达,2003,25(6).5-8.
[6]陈行勇,黎湘,郭桂荣,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.
[7] SUN Hui-xia, LIU zheng. Micro-Doppler Feature Extraction for Ballistic Missile Warhead[C].IEEE International Conference on Information and Automation.Zhangjiajie,China,2008.1333-1336.
[8] Jiajin Lei. Pattern Recognition Based on Time-Frequency Distributions of Radar Micro-Doppler Dynamics[C].IEEE Proceedings of the Sixth International Conference on SNPD/SAWN, Washington DC, USA,2005.14-18.
[9]高红卫,谢良贵,文树梁等.弹道导弹目标为多普勒特征提取[J].雷达科学与技术,2008,6(2).96-101.
[10] Sun Zhaoqiang, Li Baozhu, Lu Yaobing. Research on Mocro-Motion and Micro-Doppler of Ballistic Targets[C]. IET International Radar Conference,Guilin,China,2009,209.
[11]陈行勇,黎湘,姜斌.基于微多普勒特征的空中目标识别[J].现代雷达,2006,28(10).30-33.
[12]张顺生,曾涛.基于keystone变换的微弱目标检测[J].电子学报.2005,33(9).1675-1678。
[13]陈文驰,保铮,邢孟道.基于Keystone变换的低信噪比ISAR成像[J].西安电子科技大学学报(自然科学版).2003,4,30(2)。
[14] Pawan Setlur and Moeness Amin.Micro-doppler signal estimation for vibrating and rotating targets[J]IEEE on Signal Processing and Its Applications 2005.639-642。
[15] T. Sato. Shape Estimation of Space Debris Using Single-Range Doppler Interferometry[J]. IEEE Trans. on GRS. Mar 1999, Vol.37(2). 1000-1005。
[16] Qun Zhang,Tat Soon Yeo,Hwee Siang Tan etc. Imaging of a Moving Target With Rotating Parts Based on the Hough Transform[J]. IEEE trans. on GRS.2008 ,Vol. 46(1).pp291-299。
[17] Q. Wang, M. Xing, G. Lu, Z. Bao. High Resolution Three-Dimensional Radar Imaging for Rapidly Spinning Targets[J]. IEEE Trans. on GRS. 2008,Vol. 46(1).pp22-31。
[18] Q. Wang,M. Xing,G. Lu, Z. Bao .SRMF-CLEAN Imaging Algorithm for Space Debris[J]. IEEE Trans. on AP. 2007, Dec .Vol.55(12). 3524-3534。
[19] Chengjie Cai, Weixian Liu, Jeffrey S. Fu,et al..Empirical Mode Decomposition of Micro-Doppler Signature[C]. Proceedings of Internaltional Conference on Radar, Washington, USA, May 2005,895—899。
[20] N. E. Huang, Z. Shen, S. R. Long, et al.The Empirical Mode Decomposition and Hilbert Spectrum for Nonlinear and Non-stationary Time Series Analysis[J]. Proc. R.Soc. London A, 1998.903-995。
[21]刘永祥,黎湘,庄钊文.文导弹防御系统中的雷达目标识别研究[J].国防科技大学学报.2004,26(4).6-9。
[22]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.2006,10,25(5).360-363。
[23] LovettA, Shen C, OtaguroW. Micro-doppler: non-cooperative target classification /identification[R]. A420040, AD,Maryland, USA: Naval Air Warfare Center Aircraft Division.2004。
[24]刘永祥,黎湘,庄钊文.空间目标进动特性及在雷达识别中的应用[J].自然科学进展.2004,1.14(11).1329-1332。
[25] Cheryl Resch,Fernando J. Pineda,and I-Jeng Wang.Automatic Recognition and Assignment of Missile Pieces in Clutter[J].IEEE,1999.3177-3181。
[26] Hongying Hu,Jing Kang,and Lina Guan.Instantaneous Frequency Estimation Based on Empirical Mode Decomposition[C].Preceedings of the 7th World Congress on Intelligent Control and Automation.2008,6.3049-3051。
[27] Yongrui Zheng, Qiuhua Lin,Fuliang Yin,et al. Speech Enhancement Using ICA with EMD-Based Reference[J].Springer-Verlag Berlin Heidelberg.ICA2006,LNCS 3889.739-746.
[28] Liang, H. L., Lin, Q. H., and Chen, J. D. Z. Application of the empirical mode decompositionto the analysis of esophageal manometric data in gastroesophageal reflux disease[J].IEEE Transactions on Biomedical Engineering. 2005, vol. 52(10). 1692–1701.
[29]陈行勇.微动目标雷达特征提取技术研究.国防科技大学博士学位论文.2006。
[30]高如云,陆曼茹,张企民,等.通信电子线路[书].西安电子科技大学出版社,第八章.2002.192-196.