基于非起伏目标的相参积累TBD方法研究
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摘要
近年来,目标雷达反射截面积(RCS)减小了一到两个数量级,进而降低了目标发现概率。面对弱小目标的威胁,检测前跟踪(TBD)方法是一种有效的目标检测技术。然而现有的TBD方法在多帧回波间进行联合处理时均使用了非相参积累,使得算法积累效率较低,在低信噪比情况下往往需要对较多帧的回波进行处理才能得到较好的检测效果,数据处理量大,实时性差。
本论文针对上述问题对TBD方法进行了研究。通过分析相参雷达的多帧回波数据模型及相参积累的前提条件,针对非起伏目标提出了三种基于多帧间相参积累的TBD方法。这些方法通过多帧回波的相参积累实现了输出SNR的提高。基于相参积累的TBD方法改善了目标能量的积累效率,能够在较少帧的回波数据下有效的提高目标的发现概率。本文的主要内容有:
1.研究了多帧回波相参积累TBD方法的可行性及存在的困难。首先建立了多帧回波的相参数据模型,通过数据模型的分析,指出多帧回波相参积累的TBD方法理论上切实可行。然后对相参积累TBD方法存在的技术难点进行了分析,指出在相参积累过程中减少噪声对能量积累的影响、补偿目标回波走动及改善相参TBD方法算法复杂度等问题是实现相参TBD方法所需要解决的困难。
2.提出了三种基于相参积累的TBD方法。针对相参积累TBD方法所面临的困难,文章在多帧回波数据下通过数据拼接、回波方位选取及噪声置零、走动补偿等措施实现了多帧回波间的相参积累。根据距离走动补偿方法的不同分别提出了基于径向速度估计的相参积累TBD方法、基于radon变换的相参积累TBD方法以及基于keystone变换的相参积累TBD方法。详细介绍了三种方法的原理、处理流程及优缺点;最后通过仿真实验验证了三种算法的有效性并通过仿真实验对三种相参积累TBD方法的性能进行了比较,指出基于keystone变换的相参积累TBD方法检测性能良好且运算量小,为三种方法中最优。。
3.相参积累TBD方法实时性研究。针对基于keystone变换的相参积累TBD方法运算复杂的问题,在合理的雷达系统参数范围内,对该方法进行了算法优化,并设计了相应的并行处理流程,使得该方法运行时间大大缩短。
In the recent few years, the RCS magnitude of radar has decreased for one to two times through the stealth measures. All these treatments make them difficult to be found. Facing the threat of weak targets, the track-before-detect skill has a good effect. However, the existing TBD methods use non-coherent integration among multi-frame echoes and they have low effect in detection. So it need more date to get wonderful result and this causing the complexity computation.
According to the above problem, in this paper we make a study of TBD using coherent integration. In the studying, we analysis the model of echoes and indicate the problems of coherent integration then we gave a research of coherent TBD method. For the features of weak targets, this technology enhances the target SNR by coherent integrating of multi-frame echo. This process can further improve the detection probability of enemy targets with less data.
The main contents are as follows:
a) Researched the feasibility of coherent TBD method and its difficulties. First, We gave the coherent mathematical model and analyzed the coherent TBD method, indicated that the method is practicable. Then the difficulty of the idea was analyzed. It pointed out that the less target echo, target migration and complexity computation were the problems that the method needing to solve.
b) Proposed three methods of TBD basing coherent integration. For the problems of coherent TBD, after connected multi-frame echoes, selected the azimuth, zeroed the noise and compensated migration, the method realized coherent integration by FFT. In this paper three coherent TBD methods were proposed according the difference of compensation method: coherent integration TBD method basing velocity estimating; coherent integration TBD method basing radon transforming and coherent integration TBD method basing keystone transforming. And the thesis discussed the processes and principles of these methods in detailed. At last, thesis tested and verified that these new methods through simulation and compared the performance of these three methods through simulation experiment at first, and pointed out that the coherent integration TBD method basing keystone transforming is the best..
c) Researched the instantaneity of coherent TBD. For the problem of complexity computation, thesis analyzed the system parameters design. Under these parameters we gave a parallel processing program which reduced the running time of coherent TBD method.
本论文针对上述问题对TBD方法进行了研究。通过分析相参雷达的多帧回波数据模型及相参积累的前提条件,针对非起伏目标提出了三种基于多帧间相参积累的TBD方法。这些方法通过多帧回波的相参积累实现了输出SNR的提高。基于相参积累的TBD方法改善了目标能量的积累效率,能够在较少帧的回波数据下有效的提高目标的发现概率。本文的主要内容有:
1.研究了多帧回波相参积累TBD方法的可行性及存在的困难。首先建立了多帧回波的相参数据模型,通过数据模型的分析,指出多帧回波相参积累的TBD方法理论上切实可行。然后对相参积累TBD方法存在的技术难点进行了分析,指出在相参积累过程中减少噪声对能量积累的影响、补偿目标回波走动及改善相参TBD方法算法复杂度等问题是实现相参TBD方法所需要解决的困难。
2.提出了三种基于相参积累的TBD方法。针对相参积累TBD方法所面临的困难,文章在多帧回波数据下通过数据拼接、回波方位选取及噪声置零、走动补偿等措施实现了多帧回波间的相参积累。根据距离走动补偿方法的不同分别提出了基于径向速度估计的相参积累TBD方法、基于radon变换的相参积累TBD方法以及基于keystone变换的相参积累TBD方法。详细介绍了三种方法的原理、处理流程及优缺点;最后通过仿真实验验证了三种算法的有效性并通过仿真实验对三种相参积累TBD方法的性能进行了比较,指出基于keystone变换的相参积累TBD方法检测性能良好且运算量小,为三种方法中最优。。
3.相参积累TBD方法实时性研究。针对基于keystone变换的相参积累TBD方法运算复杂的问题,在合理的雷达系统参数范围内,对该方法进行了算法优化,并设计了相应的并行处理流程,使得该方法运行时间大大缩短。
In the recent few years, the RCS magnitude of radar has decreased for one to two times through the stealth measures. All these treatments make them difficult to be found. Facing the threat of weak targets, the track-before-detect skill has a good effect. However, the existing TBD methods use non-coherent integration among multi-frame echoes and they have low effect in detection. So it need more date to get wonderful result and this causing the complexity computation.
According to the above problem, in this paper we make a study of TBD using coherent integration. In the studying, we analysis the model of echoes and indicate the problems of coherent integration then we gave a research of coherent TBD method. For the features of weak targets, this technology enhances the target SNR by coherent integrating of multi-frame echo. This process can further improve the detection probability of enemy targets with less data.
The main contents are as follows:
a) Researched the feasibility of coherent TBD method and its difficulties. First, We gave the coherent mathematical model and analyzed the coherent TBD method, indicated that the method is practicable. Then the difficulty of the idea was analyzed. It pointed out that the less target echo, target migration and complexity computation were the problems that the method needing to solve.
b) Proposed three methods of TBD basing coherent integration. For the problems of coherent TBD, after connected multi-frame echoes, selected the azimuth, zeroed the noise and compensated migration, the method realized coherent integration by FFT. In this paper three coherent TBD methods were proposed according the difference of compensation method: coherent integration TBD method basing velocity estimating; coherent integration TBD method basing radon transforming and coherent integration TBD method basing keystone transforming. And the thesis discussed the processes and principles of these methods in detailed. At last, thesis tested and verified that these new methods through simulation and compared the performance of these three methods through simulation experiment at first, and pointed out that the coherent integration TBD method basing keystone transforming is the best..
c) Researched the instantaneity of coherent TBD. For the problem of complexity computation, thesis analyzed the system parameters design. Under these parameters we gave a parallel processing program which reduced the running time of coherent TBD method.
引文
[1].徐绵起,李侠,朱健平,端峰.现代雷达装备的发展方向.火力与指挥控制,2003,1002-0640-(2003).
[2]. Norman R. Augustine. Detection & Ranging Radar in the 20th Century. IEEE 261 Aerospace & Electronic Systems Magazine, Jubilee Issue. Oct.2000. 27-44.
[3].蒋庆全,反隐身雷达纵览,中国电子科技集团公司第28研究所,2005.
[4].傅全有.深入研究世界新军事变革大力推进我军质量建设.军事学术,2002, 29(6):3-11
[5].黄红平,强杂波下微弱目标检测算法研究:[硕士学位论文],电子科技大学,2010
[6].郭少南,强杂波下微弱目标检测技术研究:[硕士学位论文],电子科技大学,2009
[7]. Mark A.. Richards.雷达信号处理基础.邢孟道,王彤,李真芳等译.北京电子工业出版社,2006
[8]. Minkler G, Minkler J. The Principles of Automatic Radar Detection in Clutter-CFAR. Baltimore, MD: Magellan Book Company, 1990
[9]. Marcum J L, A Stastical Theory of Detection by Pulsed Radar and Mathematical Appendix. IRE Trans. on IT, 1960,6(2):259~267
[10]. North D O. An Analysis of the Factors which Determine signal/Noise Discrimination in Pulsed Carrier Systems. Proc. IEEE, 1963,51:1015~1028
[11].陈国良,孙广中,徐云,吕敏,并行算法研究方法学,计算机学报,2008,31(9)
[12]. Levanon, N. Radar Principles. Wiley, New York, 1988
[13]. Schleler D C. Automatic Detection and Radar Data Processing. Deham, Mass.: Artech House, 1980
[14]. Miller, K.; Bernstein, R. An analysis of coherent integration and its application to signal detection. IRE Transactions, 2003, vol3, pp237.
[15].丁鹭飞,耿富录.雷达原理.修订版.西安:西安电子科技大学出版社,2001,10. 133-290
[16]. Wallace, W. R. The use of track-before-detect in pulse-doppler radar. In Radar 2002,315-319.
[17]. Buzzi, S., Lops, M., and Venturino, L. Track-before-detect Procedures for Early Detection of Moving Target from Airborne Radars. Proceedings of the Radar 2004 Conference, Toulouse, France, Oct. 2004.
[18]. Stefano Buzzi, Marco Lops, Luca Venturino. Track-before-detect Procedures for EarlyDetection of Moving Target from Airborne Radars. IEEE Trans on aerospace and electronic systems, vol.41. no.3 July 2005
[19]. Dagao Duan, Meng Xie, Qian Mo. An improved Hough transform for line detection. 2010 International Conference. vol2. pp.v2-354.
[20]. Lanling Wei, Xiaoling Zhang, Ling Fan. A TBD algorithm based on improved Randomized Hough Transform for dim target detection. 2010 2nd International Conference. vol2. pp. V2-241 - V2-245
[21]. Huang Hongping, Zhang Xiaoling, Guo Shaonan. An improved TBD method based modified Hough transform and Viterbi algorithm for early detection of dim target. Radar Conference, 2009 IET International. pp.1-5
[22]. Barniv Y. Dynamic Programming Solution for Detecting Dim Moving Targets. Aerospace and Electronic Systems, IEEE Transactions on, 1985, AES-21(1):144-156
[23].李斌,彭嘉雄.基于动态规划的红外小目标检测与识别.华中理工大学学报,2000,28(06):67-70.
[24]. Yair Barniv. Dynamic programming solution for detecting dim moving target. IEEE Trans. on AES. 1985,21(1).144-155.
[25]. Johnston L A, Krishnamurthy V. Performance analysis of a dynamic programming track-before-detect algorithm. IEEE Transactions on Aerospace and Electronic Systems, 2002, 38(1).228-241.
[26]. Y. Boers, J. N. Driessen. Multi-target particle filter track-before-detect application. IEE Proceedings of Radar Sonar Navig. 12, 2004. 151(6). 351-357
[27]. Boers Y,Driessen J N.Particle Filter Based Detection for Tracking[C].Proceedings of the American Control Conference,Arlington,VA,June 25-27,2001:4393-4397.
[28]. T. Clapp and S. Godsill, Improvement strategies for monte carlo particle filters, New York: Spring-Verlag, 2001
[29].何友,关键,彭应宁等,雷达自动检测与CFAR处理,北京,第一版,清华大学出版社,1999.
[30].林文峰.雷达动目标检测研究与应用.西安电子科技大学. 2004年1月. 6-7.
[31].保铮,邢孟道,王彤.雷达成像技术.北京:电子工业出版社,2005.
[32].李海,吴嗣亮,莫力.微弱信号长时间积累的检测方法[J].北京理工大学报.2001,21(5):614-617.
[33]. Brown, W. M. and Fredricks, R. J., Range-Doppler Imaging with Motion Through ResolutionCells, IEEE Transactions on Aerospace and Electronic Systems, AES-5, no.1, p.98-102.
[34]. C. C. Chen and H. C. Andrews, Target Motion Induced Radar Imaging, IEEE Trans on AES, vol. 16, pp.2-14, 1980
[35]. Stefano Buzzi, Marco Lops, Luca Venturino. Track-before-detect Procedures for Early Detection of Moving Target from Airborne Radars. IEEE Trans on aerospace and electronic systems, vol.41. no.3 July 2005
[36]. Fengsen Deng, Xuegang Wang, "Coherent integration detection algorithm research of space debris", CIE’06 International Radar Conference, pp.I-4. (2006).
[37]. Carretero-Moya, J, Gismero-Menoyo, J, Asensio-Lopez, A,Blancodel-Campo,A. "Application of the radon transform to detect small targets in sea clutter ",Radar, Sonar & Navigation, IET, vol.3, no.2, pp. 155-166, April 2009.
[38].徐瑞,Radon变换在车牌倾斜校正中的应用,中国科技信息,2009(12)
[39]. Lian Cai, Sidan Du. Rotation,scale and translation invariant image watermarking using Radon transform and Fourier transform. 2004, Proceedings of the IEEE 6th Circuits and Systems Symposium, vol.1, pp.281.
[40]. Qinghua Ye, Raining Huang, Xinyi He, Chimhua Zhang. A SR-based radon transform to extract weak lines from noise images. ICIP 2003 International Conference. vol.1, pp.1
[41].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.
[42]. S.S. Zhang, T. Zeng. Weak Target Detection Based on Keystone Transform. Acta Electronica Sinicia, 2005,33(9). pp.1675-1678
[43]. S. Zhang, T. Zeng, T. Long, and H. Yuan, Dim target detection based on keystone transform, presented at Radar Conference, 2005
[44]. Chen Wen-chi, Bao Zheng, Xing Meng-dao, Keystone transformation based ISAR imaging at low SNR level. JOURNAL OF XIDIAN UNIVERSITY, vol.30, No.2, Apr.2003, pp.155-159.
[45]. Sun Zhaoqiang, Yu Zhong, Li Baozhu. Research on application of Keystone transform in radar. 2nd Asian-Pacific Conference. Oct.2009 page.334.
[46]. Zhaoping Wu, Xuehui He, Tao Su, Coherent Integration Detection of Multiple High Speed Targets With Range Migration and Doppler Spread. Radar Conference, 2009 IET International, page(s):1-5
[47].苏军海,李亚超,邢孟道.窄带雷达高速多目标检测研究,西安电子科技大学学报(自然科学版),2009,12. vol.36, no.6
[48]. T. L. Marzetta, E.A.Martinsen and C.P.Plum, Fast pulse Doppler radar processing accountingfor range migration, IEEE National Radar Conference, pp.264-266. (1993)
[49].陈国良,孙广中,徐云,吕敏,并行算法研究方法学,计算机学报,2008,31(9)
[50].王盛利,李世国,倪晋麟等,一种新的变换-离散匹配傅里叶变换,电子学报,2001
[2]. Norman R. Augustine. Detection & Ranging Radar in the 20th Century. IEEE 261 Aerospace & Electronic Systems Magazine, Jubilee Issue. Oct.2000. 27-44.
[3].蒋庆全,反隐身雷达纵览,中国电子科技集团公司第28研究所,2005.
[4].傅全有.深入研究世界新军事变革大力推进我军质量建设.军事学术,2002, 29(6):3-11
[5].黄红平,强杂波下微弱目标检测算法研究:[硕士学位论文],电子科技大学,2010
[6].郭少南,强杂波下微弱目标检测技术研究:[硕士学位论文],电子科技大学,2009
[7]. Mark A.. Richards.雷达信号处理基础.邢孟道,王彤,李真芳等译.北京电子工业出版社,2006
[8]. Minkler G, Minkler J. The Principles of Automatic Radar Detection in Clutter-CFAR. Baltimore, MD: Magellan Book Company, 1990
[9]. Marcum J L, A Stastical Theory of Detection by Pulsed Radar and Mathematical Appendix. IRE Trans. on IT, 1960,6(2):259~267
[10]. North D O. An Analysis of the Factors which Determine signal/Noise Discrimination in Pulsed Carrier Systems. Proc. IEEE, 1963,51:1015~1028
[11].陈国良,孙广中,徐云,吕敏,并行算法研究方法学,计算机学报,2008,31(9)
[12]. Levanon, N. Radar Principles. Wiley, New York, 1988
[13]. Schleler D C. Automatic Detection and Radar Data Processing. Deham, Mass.: Artech House, 1980
[14]. Miller, K.; Bernstein, R. An analysis of coherent integration and its application to signal detection. IRE Transactions, 2003, vol3, pp237.
[15].丁鹭飞,耿富录.雷达原理.修订版.西安:西安电子科技大学出版社,2001,10. 133-290
[16]. Wallace, W. R. The use of track-before-detect in pulse-doppler radar. In Radar 2002,315-319.
[17]. Buzzi, S., Lops, M., and Venturino, L. Track-before-detect Procedures for Early Detection of Moving Target from Airborne Radars. Proceedings of the Radar 2004 Conference, Toulouse, France, Oct. 2004.
[18]. Stefano Buzzi, Marco Lops, Luca Venturino. Track-before-detect Procedures for EarlyDetection of Moving Target from Airborne Radars. IEEE Trans on aerospace and electronic systems, vol.41. no.3 July 2005
[19]. Dagao Duan, Meng Xie, Qian Mo. An improved Hough transform for line detection. 2010 International Conference. vol2. pp.v2-354.
[20]. Lanling Wei, Xiaoling Zhang, Ling Fan. A TBD algorithm based on improved Randomized Hough Transform for dim target detection. 2010 2nd International Conference. vol2. pp. V2-241 - V2-245
[21]. Huang Hongping, Zhang Xiaoling, Guo Shaonan. An improved TBD method based modified Hough transform and Viterbi algorithm for early detection of dim target. Radar Conference, 2009 IET International. pp.1-5
[22]. Barniv Y. Dynamic Programming Solution for Detecting Dim Moving Targets. Aerospace and Electronic Systems, IEEE Transactions on, 1985, AES-21(1):144-156
[23].李斌,彭嘉雄.基于动态规划的红外小目标检测与识别.华中理工大学学报,2000,28(06):67-70.
[24]. Yair Barniv. Dynamic programming solution for detecting dim moving target. IEEE Trans. on AES. 1985,21(1).144-155.
[25]. Johnston L A, Krishnamurthy V. Performance analysis of a dynamic programming track-before-detect algorithm. IEEE Transactions on Aerospace and Electronic Systems, 2002, 38(1).228-241.
[26]. Y. Boers, J. N. Driessen. Multi-target particle filter track-before-detect application. IEE Proceedings of Radar Sonar Navig. 12, 2004. 151(6). 351-357
[27]. Boers Y,Driessen J N.Particle Filter Based Detection for Tracking[C].Proceedings of the American Control Conference,Arlington,VA,June 25-27,2001:4393-4397.
[28]. T. Clapp and S. Godsill, Improvement strategies for monte carlo particle filters, New York: Spring-Verlag, 2001
[29].何友,关键,彭应宁等,雷达自动检测与CFAR处理,北京,第一版,清华大学出版社,1999.
[30].林文峰.雷达动目标检测研究与应用.西安电子科技大学. 2004年1月. 6-7.
[31].保铮,邢孟道,王彤.雷达成像技术.北京:电子工业出版社,2005.
[32].李海,吴嗣亮,莫力.微弱信号长时间积累的检测方法[J].北京理工大学报.2001,21(5):614-617.
[33]. Brown, W. M. and Fredricks, R. J., Range-Doppler Imaging with Motion Through ResolutionCells, IEEE Transactions on Aerospace and Electronic Systems, AES-5, no.1, p.98-102.
[34]. C. C. Chen and H. C. Andrews, Target Motion Induced Radar Imaging, IEEE Trans on AES, vol. 16, pp.2-14, 1980
[35]. Stefano Buzzi, Marco Lops, Luca Venturino. Track-before-detect Procedures for Early Detection of Moving Target from Airborne Radars. IEEE Trans on aerospace and electronic systems, vol.41. no.3 July 2005
[36]. Fengsen Deng, Xuegang Wang, "Coherent integration detection algorithm research of space debris", CIE’06 International Radar Conference, pp.I-4. (2006).
[37]. Carretero-Moya, J, Gismero-Menoyo, J, Asensio-Lopez, A,Blancodel-Campo,A. "Application of the radon transform to detect small targets in sea clutter ",Radar, Sonar & Navigation, IET, vol.3, no.2, pp. 155-166, April 2009.
[38].徐瑞,Radon变换在车牌倾斜校正中的应用,中国科技信息,2009(12)
[39]. Lian Cai, Sidan Du. Rotation,scale and translation invariant image watermarking using Radon transform and Fourier transform. 2004, Proceedings of the IEEE 6th Circuits and Systems Symposium, vol.1, pp.281.
[40]. Qinghua Ye, Raining Huang, Xinyi He, Chimhua Zhang. A SR-based radon transform to extract weak lines from noise images. ICIP 2003 International Conference. vol.1, pp.1
[41].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.
[42]. S.S. Zhang, T. Zeng. Weak Target Detection Based on Keystone Transform. Acta Electronica Sinicia, 2005,33(9). pp.1675-1678
[43]. S. Zhang, T. Zeng, T. Long, and H. Yuan, Dim target detection based on keystone transform, presented at Radar Conference, 2005
[44]. Chen Wen-chi, Bao Zheng, Xing Meng-dao, Keystone transformation based ISAR imaging at low SNR level. JOURNAL OF XIDIAN UNIVERSITY, vol.30, No.2, Apr.2003, pp.155-159.
[45]. Sun Zhaoqiang, Yu Zhong, Li Baozhu. Research on application of Keystone transform in radar. 2nd Asian-Pacific Conference. Oct.2009 page.334.
[46]. Zhaoping Wu, Xuehui He, Tao Su, Coherent Integration Detection of Multiple High Speed Targets With Range Migration and Doppler Spread. Radar Conference, 2009 IET International, page(s):1-5
[47].苏军海,李亚超,邢孟道.窄带雷达高速多目标检测研究,西安电子科技大学学报(自然科学版),2009,12. vol.36, no.6
[48]. T. L. Marzetta, E.A.Martinsen and C.P.Plum, Fast pulse Doppler radar processing accountingfor range migration, IEEE National Radar Conference, pp.264-266. (1993)
[49].陈国良,孙广中,徐云,吕敏,并行算法研究方法学,计算机学报,2008,31(9)
[50].王盛利,李世国,倪晋麟等,一种新的变换-离散匹配傅里叶变换,电子学报,2001