机动目标跟踪波形和检测门限自适应算法
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摘要
由于现有雷达目标跟踪波形和检测门限自适应算法大多围绕以距离、距离率作为量测的一维运动目标展开,忽略了角度对目标跟踪的影响,从而无法对目标进行跟踪定位。为此,提出一种杂波背景下针对二维机动目标跟踪的雷达波形和检测门限联合自适应算法。首先,对传统基于时延-多普勒分辨单元的理论作进一步扩展,设计出一种包含距离-距离率和方位为量测的具有"棱柱"结构的分辨单元;然后,给出了包含波形参数和检测门限的量测误差协方差的联合近似表达式;最后,利用认知雷达思想,以滤波误差协方差的迹最小为代价函数自适应选择下一时刻的波形参数和检测门限,以提高系统的跟踪性能。仿真结果表明,波形和检测门限联合自适应算法的跟踪性能要明显优于传统的固定参数跟踪算法。
The existing adaptive waveform and detection threshold algorithms for radar target tracking focus mostly on the one-dimensional target with the range and range rate as measurements.As it ignores the effect of the angle on target tracking,it is impossible to track and locate the target.A joint adaptive waveform and detection threshold algorithm for two-dimensional maneuvering target tracking in clutter background is proposed.First,the traditional theory based on the time delay-Doppler resolution cell is further extended to design a resolution cell with the"prism"structure,which includes the range-range rate and azimuth measurements.Then,an approximate joint expression for measurement error covariance,containing the waveform parameter and detection threshold,is given.Finally,inspired by the cognitive radar,the next waveform parameters and detection threshold are adaptively selected at the cost of minimizing the trace of filtering error covariance to improve the tracking performance of the system.Simulation results show that the performance of the waveform and detection threshold self-adaption algorithm is obviously superior to the fixed parameter algorithm.
The existing adaptive waveform and detection threshold algorithms for radar target tracking focus mostly on the one-dimensional target with the range and range rate as measurements.As it ignores the effect of the angle on target tracking,it is impossible to track and locate the target.A joint adaptive waveform and detection threshold algorithm for two-dimensional maneuvering target tracking in clutter background is proposed.First,the traditional theory based on the time delay-Doppler resolution cell is further extended to design a resolution cell with the"prism"structure,which includes the range-range rate and azimuth measurements.Then,an approximate joint expression for measurement error covariance,containing the waveform parameter and detection threshold,is given.Finally,inspired by the cognitive radar,the next waveform parameters and detection threshold are adaptively selected at the cost of minimizing the trace of filtering error covariance to improve the tracking performance of the system.Simulation results show that the performance of the waveform and detection threshold self-adaption algorithm is obviously superior to the fixed parameter algorithm.
引文
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[12]WANG J T,QIN Y L,WANG H Q,et al.Dynamic Waveform Selection for Manoeuvering Target Tracking in Clutter[J].IET Radar,Sonar and Navigation,2013,7(7):815-825.
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[2]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,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,2014,41(1):57-63.
[3]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 Huailin.Waveform Self-adaption Data Association Algorithm for Cognitive Radar Tracking[J].Journal of Astronautics,2017,38(12):1331-1338.
[4]HAYKIN S.Cognitive Radar:A Way of the Future[J].IEEE Signal Processing Magazine,2006,23(1):30-40.
[5]WU X,CHEN J,LU K.Investigation of System Structure and Information Processing Mechanism for Cognitive Skywave Over-the-Horizon Radar[J].Journal of Systems Engineering and Electronics,2016,27(4):797-806.
[6]KILANI M B,NIJSURE Y,GAGNON G,et al.Cognitive Waveform and Receiver Selection Mechanism for Multistatic Radar[J].IET Radar,Sonar and Navigation,2016,10(2):417-425.
[7]ZHANG X,WANG K,LIU X.Joint Optimisation of Transmit Waveform and Receive Filter for Cognitive Radar[J].IET Radar,Sonar and Navigation,2018,12(1):11-20.
[8]JIN B,GUO J,SU B,et al.Adaptive Waveform Selection for Maneuvering Target Tracking in Cognitive Radar[J].Digital Signal Processing,2018,75:210-221.
[9]WANG H Q,XIA H E,CHENG Y Q,et al.An Adaptive Waveform Detection Threshold Joint Optimization Method for Target Tracking[J].Journal of Central South University,2013,20(11):3057-3064.
[10]HONG S M,EVANS R J,SHIN H 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.
[11]LI X R,JILKOV V P.Survey of Maneuvering Target Tracking-Part I:Dynamic Models[J].IEEE Transactions on Aerospace and Electronic Systems,2003,39(4):1333-1364.
[12]WANG J T,QIN Y L,WANG H Q,et al.Dynamic Waveform Selection for Manoeuvering Target Tracking in Clutter[J].IET Radar,Sonar and Navigation,2013,7(7):815-825.
[13]VAN TREES H L.检测、估计和调制理论[M].张其善,毛士艺,周荫清,译.北京:电子工业出版社,2007:347-348.
[14]夏洪恩.基于目标跟踪的波形自适应选择技术[D].长沙:国防科学技术大学,2010:43-45.
[15]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,1991:278.