解决雷达方位角突变问题的一种方法
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摘要
针对雷达坐标系在特定情况会发生方位角突变,造成跟踪算法发散、降低跟踪性能的问题,提出了将量测中的方位角信息转化为方位角余弦值和正弦值,并将这两个值嵌入雷达量测中,构成修正量测。由于修正量测的协方差矩阵为奇异矩阵,该文用方位角方差构成的对角矩阵替换两个三角函数量测的协方差矩阵。仿真结果表明,修正量测及其协方差矩阵的替换对跟踪精度的影响很小,并且即使在角度突变的情况下,跟踪算法结合修正量测数据同样可以实现对目标的稳定跟踪。
Azimuth mutation is a particular situation in the radar coordinate system, ending up with the tracking algorithm diverges and the tracking performance reduces. Aiming at this problem, this paper substitutes the combined values of azimuth angel′s cosine and sine function for the azimuth angel in radar measurement. Since the covariance matrix of the modified measurement is a singular matrix, the diagonal matrix composed of the azimuth variance is used to replace the covariance matrix of the two trigonometric functions. The simulation results show that the correction measurement and its replacement of covariance matrix have little effect on the tracking accuracy, and even in the case of sudden angle change, the tracking algorithm combined with the modified measurement data can also achieve stable tracking of the target.
Azimuth mutation is a particular situation in the radar coordinate system, ending up with the tracking algorithm diverges and the tracking performance reduces. Aiming at this problem, this paper substitutes the combined values of azimuth angel′s cosine and sine function for the azimuth angel in radar measurement. Since the covariance matrix of the modified measurement is a singular matrix, the diagonal matrix composed of the azimuth variance is used to replace the covariance matrix of the two trigonometric functions. The simulation results show that the correction measurement and its replacement of covariance matrix have little effect on the tracking accuracy, and even in the case of sudden angle change, the tracking algorithm combined with the modified measurement data can also achieve stable tracking of the target.
引文
[1] 夏小虎, 刘明. 联合约束级联交互式多模型滤波器及其在机动目标跟踪中的应用[J]. 电子与信息学报, 2017, 39(1): 117-123.XIA Xiaohu, LIU Ming. Unified constrained cascade interactive multi-model filter and its application in tracking of maneuvering target[J]. Journal of Electronics & Information Technology, 2017, 39(1): 117-123.
[2] 杨峰, 张婉莹. 一种多模型贝努利粒子滤波机动目标跟踪算法[J]. 电子与信息学报, 2017, 39(3): 634-639. YANG Feng, ZHANG Wanying. Multiple model bernoulli particle filter for maneuvering target tracking[J]. Journal of Electronics & Information Technology, 2017, 39(3): 634-639.
[3] DUAN Z, HAN C, LI X R. Comments on ′Unbiased converted measurements for tracking[J]. IEEE Transactions on Aerospace & Electronic Systems, 2008, 40(4): 1374-1376.
[4] BORDONARO S V, WILLETT P, BAR SHALOM Y. Unbiased tracking with converted measurements[C]// Radar Conference. Atlanta Georgia: IEEE Press, 2012: 741-745.
[5] BORDONARO S V, WILLETT P, BAR SHALOM Y. Decorrelated unbiased converted measurement Kalman filter[J]. IEEE Transactions on Aerospace & Electronic Systems, 2014, 50(2): 1431-1444.
[6] WEI Mei, BAR SHALOM Y. Unbiased Kalman filter using converted measurements: revisit[J]. Proceedings of SPIE-The International Society for Optical Engineering, 2009, 7445: 1-9.
[7] BORDONARO S, WILLETT P, BAR SHALOM Y. Consistent linear tracker with converted range, bearing and range rate measurements[J]. IEEE Transactions on Aerospace & Electronic Systems, 2017, 99(16): 1.
[8] WU W, JIANG J, LIU W, et al. A sequential converted measurement Kalman filter in the ECEF coordinate system for airborne Doppler radar[J]. Aerospace Science & Technology, 2016, 51(1): 11-17.
[9] SUBEDI S, ZHANG Y D, AMIN M G, et al. Group sparsity based multi-target tracking in passive multi-static radar systems using Doppleronly measurements[J]. IEEE Transactions on Signal Processing, 2016, 64(14): 3619-3634.
[10] GULDOGAN M B, LINDGREN D, GUSTAFSSON F, et al. Multi-target tracking with PHD filter using Doppler-only measurements[J]. Digital Signal Processing, 2014, 27(4): 1-11.
[11] JU H Y, DU Y K, BAE S H, et al. Joint initialization and tracking of multiple moving objects using Doppler information[J]. IEEE Transactions on Signal Processing, 2011, 59(7): 3447-3452.
[12] GOLUB G, CHARLES V L. Matrix computation[M]. 4th edition. Beijing: Posts & Telecom Press, 2014: 153-233.
[13] ZHAO J, NETTO M, MILI L. A robust iterated extended Kalman filter for power system dynamic state estimation[J]. IEEE Transactions on Power Systems, 2017, 32(4): 3205-3216.
[14] AMBROSINO R, BASELICE F, FERRAIOLI G, et al. Extended Kalman filter for multichannel InSAR height reconstruction[J]. IEEE Transactions on Geoscience & Remote Sensing, 2017, 99(1): 1-10.
[15] ZHAO J B. Dynamic state estimation with model uncertainties using H-infinity extended Kalman filter[J]. IEEE Transactions on Power Systems, 2017, 99(2): 1.
[16] SABET M T, FATHI A R, DANIALI H R M. Optimal design of the own ship maneuver in the bearing-only target motion analysis problem using a heuristically supervised extended Kalman filter[J]. Ocean Engineering, 2016, 123(1): 146-153.
[2] 杨峰, 张婉莹. 一种多模型贝努利粒子滤波机动目标跟踪算法[J]. 电子与信息学报, 2017, 39(3): 634-639. YANG Feng, ZHANG Wanying. Multiple model bernoulli particle filter for maneuvering target tracking[J]. Journal of Electronics & Information Technology, 2017, 39(3): 634-639.
[3] DUAN Z, HAN C, LI X R. Comments on ′Unbiased converted measurements for tracking[J]. IEEE Transactions on Aerospace & Electronic Systems, 2008, 40(4): 1374-1376.
[4] BORDONARO S V, WILLETT P, BAR SHALOM Y. Unbiased tracking with converted measurements[C]// Radar Conference. Atlanta Georgia: IEEE Press, 2012: 741-745.
[5] BORDONARO S V, WILLETT P, BAR SHALOM Y. Decorrelated unbiased converted measurement Kalman filter[J]. IEEE Transactions on Aerospace & Electronic Systems, 2014, 50(2): 1431-1444.
[6] WEI Mei, BAR SHALOM Y. Unbiased Kalman filter using converted measurements: revisit[J]. Proceedings of SPIE-The International Society for Optical Engineering, 2009, 7445: 1-9.
[7] BORDONARO S, WILLETT P, BAR SHALOM Y. Consistent linear tracker with converted range, bearing and range rate measurements[J]. IEEE Transactions on Aerospace & Electronic Systems, 2017, 99(16): 1.
[8] WU W, JIANG J, LIU W, et al. A sequential converted measurement Kalman filter in the ECEF coordinate system for airborne Doppler radar[J]. Aerospace Science & Technology, 2016, 51(1): 11-17.
[9] SUBEDI S, ZHANG Y D, AMIN M G, et al. Group sparsity based multi-target tracking in passive multi-static radar systems using Doppleronly measurements[J]. IEEE Transactions on Signal Processing, 2016, 64(14): 3619-3634.
[10] GULDOGAN M B, LINDGREN D, GUSTAFSSON F, et al. Multi-target tracking with PHD filter using Doppler-only measurements[J]. Digital Signal Processing, 2014, 27(4): 1-11.
[11] JU H Y, DU Y K, BAE S H, et al. Joint initialization and tracking of multiple moving objects using Doppler information[J]. IEEE Transactions on Signal Processing, 2011, 59(7): 3447-3452.
[12] GOLUB G, CHARLES V L. Matrix computation[M]. 4th edition. Beijing: Posts & Telecom Press, 2014: 153-233.
[13] ZHAO J, NETTO M, MILI L. A robust iterated extended Kalman filter for power system dynamic state estimation[J]. IEEE Transactions on Power Systems, 2017, 32(4): 3205-3216.
[14] AMBROSINO R, BASELICE F, FERRAIOLI G, et al. Extended Kalman filter for multichannel InSAR height reconstruction[J]. IEEE Transactions on Geoscience & Remote Sensing, 2017, 99(1): 1-10.
[15] ZHAO J B. Dynamic state estimation with model uncertainties using H-infinity extended Kalman filter[J]. IEEE Transactions on Power Systems, 2017, 99(2): 1.
[16] SABET M T, FATHI A R, DANIALI H R M. Optimal design of the own ship maneuver in the bearing-only target motion analysis problem using a heuristically supervised extended Kalman filter[J]. Ocean Engineering, 2016, 123(1): 146-153.