基于波形自适应的认知雷达机动目标跟踪算法
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摘要
从认知雷达的角度出发,综合考虑跟踪模型和波形选择,提出一种能够适应目标运动状态急剧变化的波形自适应机动目标跟踪算法。首先,将匀速运动模型和当前统计模型作为交互式多模型(IMM)的模型集,并结合贝叶斯理论提出一种时变转移概率的自适应IMM算法。然后,结合量测误差椭圆与目标状态预测误差椭圆正交理论,研究了基于基带脉冲波形模糊函数旋转的波形库实现方法并给出了波形自适应选择跟踪算法的具体步骤。仿真实验表明,所提算法能够适应目标不同加速度机动,雷达系统跟踪性能得到了较大幅度提升。
In the viewpoint of cognitive radar,a waveform-adaption maneuvering target tracking algorithm is presented. The algorithm considers both the tracking model and waveform selection to suit the intensely varying of target motion. Firstly,constant velocity( CV) model and current statistic( CS) model are used as the model sets of interacting multiple model( IMM). A time-varying transition probability adaptive IMM algorithm is proposed according to the Bayesian theory. Then,according to the orthogonal theory of measurement error ellipse and state predicted error ellipse,the method of waveform library is given,which is based on the rotation of base-band pulse waveform ambiguity function. The step to realize the waveform-adaption tracking algorithm is also given.Simulation results show that the algorithm can satisfy different maneuver of target,and the tracking performance of proposed algorithm is improved sharply.
In the viewpoint of cognitive radar,a waveform-adaption maneuvering target tracking algorithm is presented. The algorithm considers both the tracking model and waveform selection to suit the intensely varying of target motion. Firstly,constant velocity( CV) model and current statistic( CS) model are used as the model sets of interacting multiple model( IMM). A time-varying transition probability adaptive IMM algorithm is proposed according to the Bayesian theory. Then,according to the orthogonal theory of measurement error ellipse and state predicted error ellipse,the method of waveform library is given,which is based on the rotation of base-band pulse waveform ambiguity function. The step to realize the waveform-adaption tracking algorithm is also given.Simulation results show that the algorithm can satisfy different maneuver of target,and the tracking performance of proposed algorithm is improved sharply.
引文
[1] HAYKIN S. Cognitive radar:a way of the future[J]. IEEE Signal Processing Magazine,2006(23):30-40.
[2] HAYKIN S,ZIA A,ARASARATNAM I,et al. Cognitive tracking radar[C]//Radar Conference. Washington,DC:IEEE Press,2010.
[3] KERSHAW D J,EVANS R J.Optimal waveform selection for tracking systems[J]. IEEE Transactions on Information Theory,1994,40(5):1536-1550.
[4] KERSHAW D J,EVANS R J.Waveform selective probabilistic data association[J]. IEEE Transactions on Aerospace and Electronic Systems,1997,33(4):1180-1188.
[5] SUVOROVA S,HOWARD S D,MORAN W,et al. Waveform libraries for radar tracking applications:Maneuvering targets[C]//IEEE Annual Conference on Information Sciences and Systems. Princeton, NJ:IEEE Press, 2006:1424-1428.
[6] RAGO C,WILLETT P,BAR-SHALOM Y.Detection tracking performance with combined waveforms[J]. IEEE Transactions on Aerospace and Electronic Systems,1998,34(2):612-624.
[7] NIU R,WILLETT P,BAR-SHALOM Y.Tracking considerations in selection of radar waveform for range and range-rate measurements[J]. IEEE Transactions on Aerospace and Electronic Systems,2002,38(2):467-487.
[8] SAVAGE C O,MORAN B.Waveform selection for maneuvering targets within an IMM framework[J]. IEEE Transactions on Aerospace and Electronic Systems,2007,43(3):1205-1214.
[9]檀甲甲,张建秋.跟踪机动目标的雷达波形选择新方法[J].系统工程与电子技术,2011,33(3):515-522.TAN Jiajia,ZHANG Jianqiu. New waveform selection approach to tracking maneuver targets[J]. Systems Engineering and Electronics,2011,33(3):515-522.
[10] LI Wen,LI Qingdang,FAN Yao,et al. Maneuvering acceleration assisted attitude algorithm design based on fuzzy adaptive Kalman filter[C]//Proceedings of 2014 IEEE Chinese Guidance, Navigation and Control Conference.Yantai,Chian:IEEE Press,2014:1501-1505.
[11] YANG Y J,FAN X G. A new parameters adaptively adjusting method of current statistical model[C]//2015 IEEE International Conference on Information and Automation.[S.l.]:IEEE Press,2015:1738-1742.
[12] SUN Wei,YANG Yongjian. Adaptive maneuvering frequency method of current statistical model[J]. IEEE/CAA Journal of Automatic Sinica,2016,4(1):154-160.
[13]靳标,纠博,刘宏伟,等.一种针对目标跟踪的自适应波形选择方法[J].西安电子科技大学学报(自然科学版),2014,41(1):57-63.JIN Biao,JIU Bo,LIU Hongwei,et al. Adaptive waveform selection approach for target tracking[J]. Journal of Xidian University(Natural Science),2014,41(1):57-63.
[14] EUN Y,JEON D. Fuzzy interence-based dynamic determination of IMM mode transition probability for multi-radar tracking[C]//International IEEE Conference on Information Fusion. Istanbul:IEEE Press,2013:1520-1525.
[15] BI X,WANG W,GAO J,et al. The improved IMM tracking algorithm for high-speed maneuvering target[C]//Intelligent Detection and Laboratory Equipment. Hangzhou:IET Press,2015:1-3.
[16]郭志,董春云,蔡远利,等.时变转移概率IMMSRCKF机动目标跟踪算法[J].系统工程与电子技术,2015,37(1):24-30.GUO Zhi,DONG Chunyun,CAI Yuanli,et al. Time-varying transition probability based IMM-SRCKF algorithm for maneuvering target tracking[J]. Systems Engineering and Electronics,2015,37(1):24-30.
[17]周宏仁,敬忠良,王培德.机动目标跟踪[M].北京:国防工业出版社,1991:134-142.ZHOU Hongren,JING Zhongliang,WANG Peide. Tracking of maneuvering targets[M]. Beijing:National Defense Industry Press,1991:134-142.
[18]靳标.认知雷达目标跟踪方法研究[D].西安:西安电子科技大学,2009:21-27.JIN Biao. Research on target tracking methods in cognitive radar[D]. Xi'an:Xidian University,2009:21-27.
[19] SUN-MOG H,EVANS R J,HAN-SEOP S.Optimization of waveform and detection threshold for range and range-rate tracking in clutter[J]. IEEE Transactions on Aerospace and Electronic Systems,2005,41(1):17-33.
[20]王树亮,毕大平,阮怀林.认知雷达波形自适应数据关联跟踪算法[J].宇航学报,2017,38(12):1331-1338.WANG Shuliang,BI Daping,RUAN Huanlin. Waveform selfdaption data association algorithm for cognitive radar tracking[J.Journal of Astronautic,2017,38(12):1331-1338.
[2] HAYKIN S,ZIA A,ARASARATNAM I,et al. Cognitive tracking radar[C]//Radar Conference. Washington,DC:IEEE Press,2010.
[3] KERSHAW D J,EVANS R J.Optimal waveform selection for tracking systems[J]. IEEE Transactions on Information Theory,1994,40(5):1536-1550.
[4] KERSHAW D J,EVANS R J.Waveform selective probabilistic data association[J]. IEEE Transactions on Aerospace and Electronic Systems,1997,33(4):1180-1188.
[5] SUVOROVA S,HOWARD S D,MORAN W,et al. Waveform libraries for radar tracking applications:Maneuvering targets[C]//IEEE Annual Conference on Information Sciences and Systems. Princeton, NJ:IEEE Press, 2006:1424-1428.
[6] RAGO C,WILLETT P,BAR-SHALOM Y.Detection tracking performance with combined waveforms[J]. IEEE Transactions on Aerospace and Electronic Systems,1998,34(2):612-624.
[7] NIU R,WILLETT P,BAR-SHALOM Y.Tracking considerations in selection of radar waveform for range and range-rate measurements[J]. IEEE Transactions on Aerospace and Electronic Systems,2002,38(2):467-487.
[8] SAVAGE C O,MORAN B.Waveform selection for maneuvering targets within an IMM framework[J]. IEEE Transactions on Aerospace and Electronic Systems,2007,43(3):1205-1214.
[9]檀甲甲,张建秋.跟踪机动目标的雷达波形选择新方法[J].系统工程与电子技术,2011,33(3):515-522.TAN Jiajia,ZHANG Jianqiu. New waveform selection approach to tracking maneuver targets[J]. Systems Engineering and Electronics,2011,33(3):515-522.
[10] LI Wen,LI Qingdang,FAN Yao,et al. Maneuvering acceleration assisted attitude algorithm design based on fuzzy adaptive Kalman filter[C]//Proceedings of 2014 IEEE Chinese Guidance, Navigation and Control Conference.Yantai,Chian:IEEE Press,2014:1501-1505.
[11] YANG Y J,FAN X G. A new parameters adaptively adjusting method of current statistical model[C]//2015 IEEE International Conference on Information and Automation.[S.l.]:IEEE Press,2015:1738-1742.
[12] SUN Wei,YANG Yongjian. Adaptive maneuvering frequency method of current statistical model[J]. IEEE/CAA Journal of Automatic Sinica,2016,4(1):154-160.
[13]靳标,纠博,刘宏伟,等.一种针对目标跟踪的自适应波形选择方法[J].西安电子科技大学学报(自然科学版),2014,41(1):57-63.JIN Biao,JIU Bo,LIU Hongwei,et al. Adaptive waveform selection approach for target tracking[J]. Journal of Xidian University(Natural Science),2014,41(1):57-63.
[14] EUN Y,JEON D. Fuzzy interence-based dynamic determination of IMM mode transition probability for multi-radar tracking[C]//International IEEE Conference on Information Fusion. Istanbul:IEEE Press,2013:1520-1525.
[15] BI X,WANG W,GAO J,et al. The improved IMM tracking algorithm for high-speed maneuvering target[C]//Intelligent Detection and Laboratory Equipment. Hangzhou:IET Press,2015:1-3.
[16]郭志,董春云,蔡远利,等.时变转移概率IMMSRCKF机动目标跟踪算法[J].系统工程与电子技术,2015,37(1):24-30.GUO Zhi,DONG Chunyun,CAI Yuanli,et al. Time-varying transition probability based IMM-SRCKF algorithm for maneuvering target tracking[J]. Systems Engineering and Electronics,2015,37(1):24-30.
[17]周宏仁,敬忠良,王培德.机动目标跟踪[M].北京:国防工业出版社,1991:134-142.ZHOU Hongren,JING Zhongliang,WANG Peide. Tracking of maneuvering targets[M]. Beijing:National Defense Industry Press,1991:134-142.
[18]靳标.认知雷达目标跟踪方法研究[D].西安:西安电子科技大学,2009:21-27.JIN Biao. Research on target tracking methods in cognitive radar[D]. Xi'an:Xidian University,2009:21-27.
[19] SUN-MOG H,EVANS R J,HAN-SEOP S.Optimization of waveform and detection threshold for range and range-rate tracking in clutter[J]. IEEE Transactions on Aerospace and Electronic Systems,2005,41(1):17-33.
[20]王树亮,毕大平,阮怀林.认知雷达波形自适应数据关联跟踪算法[J].宇航学报,2017,38(12):1331-1338.WANG Shuliang,BI Daping,RUAN Huanlin. Waveform selfdaption data association algorithm for cognitive radar tracking[J.Journal of Astronautic,2017,38(12):1331-1338.