基于概率假设密度滤波与无迹Kalman滤波的多目标跟踪与识别

doi:10.3969/j.issn.1000-1093.2020.08.004

摘要/Abstract

摘要： 为提高导引头末制导阶段抗干扰能力，针对典型的欺骗式距离-速度联合拖引干扰模型，研究了基于概率假设密度（PHD）滤波的多目标跟踪与基于无迹Kalman滤波（UKF）的多目标识别技术。为说明导引头目标识别原理，给出了距离-速度联合拖引干扰模型；根据导引头测量原理，通过导引头框架角、导弹-目标相对距离、径向速度建立系统跟踪模型，给出了基于PHD滤波的多目标跟踪与基于UKF的多目标识别的基本原理；基于典型的目标运动模型（匀速直线与匀速转弯模型），针对目标施加的4次距离-速度联合拖引干扰，采用目标跟踪结果以及估计的目标速度和加速度信息进行多目标跟踪与识别分析，能够很快实现真假目标识别。仿真实验结果表明，利用PHD滤波与UKF信息能够有效实现对距离-速度拖引干扰下的多目标跟踪与识别。

关键词: 导引头, 航迹滤波, 目标跟踪, 目标识别, 抗干扰, 概率假设密度滤波, 无迹Kalman滤波

Abstract: For the typical range-velocity simultaneous pull-off jamming model, the multi-target tracking technology based on probability hypothesis density (PHD) filter and the multi-target recognition technology based on unscented Kalman filter (UKF) are studied to improve the anti-jamming capability of seeker in terminal guidance phase. A range-velocity simultaneous pull-off jamming model is established to explain the principle of target recognition. According to the principle of seeker measurement, a system tracking model is established， in which the frame angle of seeker, missile-target relative distance, radial velocity, elevatiom angle and azimuth angle are considered. The basic principle of multi-target tracking based on PHD filter and multi-target recognition based on UKF filter is presented. Finally, in the typical target motion model (uniform rectilinear and uniform turning model), the target velocity and acceleration information estimated by filtering can be used to identify real and false targets quickly in view of the four target range-velocity simultaneous pull-off jammings. The simulated results show that the PHD and UKF filters presented in this paper can effectively realize the multi-target recognition and tracking under range-velocity simultaneous pull-off jamming, and verify the feasibility and effectiveness of the proposed algorithm.

Key words: seeker, trackfiltering, targettracking, targetrecognition, anti-jamming, probabilityhypothesisdensityfilter, unscentedKalmanfilter

中图分类号:

TJ765.3⁺31

邹汝平，刘建书. 基于概率假设密度滤波与无迹Kalman滤波的多目标跟踪与识别[J]. 兵工学报, 2020, 41(8): 1502-1508.

ZOU Ruping， LIU Jianshu. Multi-target Tracking and Recognition Technology Based on PHD and UKF[J]. Acta Armamentarii, 2020, 41(8): 1502-1508.

参考文献［1］

［1］

姚杰平. 雷达抗有源干扰的方法研究[D]. 西安: 西安电子科技大学, 2012.YAO J P. Research on anti-jamming of active deception[D]. Xi'an: Xidian University, 2012.(in Chinese)[2］郭琴. 超高速目标雷达探测下的距离-速度同步假目标抗干扰[D]. 北京: 北京理工大学, 2016.GUO Q. The method against range-velocity false targets under the ultra-high speed targets detection of radar[D]. Beijing: Beijing Institute of Technology, 2016. (in Chinese)[3］刘勇, 刘忠, 傅其祥, 等. 距离-速度同步拖引干扰的数字实现方法[J]. 航天电子对抗, 2007, 23(1): 46-49.LIU Y, LIU Z, FU Q X, et al. A digital implementing method for range-velocity simultaneous pull-off[J]. Aerospace Electronic Warfare, 2007, 23(1): 46-49.(in Chinese)[4］ ZHAO L, SUN J P, XU X J, et al. Space-time adaptive processing for sea clutter and jamming suppression in radar seekers[C]∥Proceedings of the 2nd International Conference on Signal Processing Systems. Dalian, China: IEEE, 2010: 600-604.[5］ BABY E, BHARGAVE A A. Space time adaptive processing for clutter suppression in radar using subspace based technique[J]. International Journal of Technical Research and Applications, 2014, 2(3):163-168.[6］ SEDYSHEV Y N, GORDIENKO V N. The coherent biostatic radar with multi-stage space-time adaptive processing of signals and jamming[C]∥Proceedings of the IEEE 2000 International Radar Conference. Alexandria, VA, US: IEEE, 2000: 329-334.[7］成霄亮. 制导雷达抗有源欺骗干扰方法研究[D]. 长沙：湖南大学, 2014.CHENG X L. Method study of anti-jamming of active deception in radar guidance[D]. Changsha: Hunan University, 2014. (in Chinese)[8］贾舒宜, 王子玲, 唐田田. 距离_速度同步欺骗干扰下的机动目标跟踪算法[J]. 系统工程与电子技术, 2017, 39(9): 1942-1949. JIA S Y, WANG Z L, TANG T T. Research on tracking of maneuvering targets in simultaneous range and velocity jamming[J]. Systems Engineering and Electronics, 2017, 39(9): 1942-1949. (in Chinese)[9］王铮, 韩宝玲. 基于UKF航迹滤波的干扰目标智能识别算法研究[J]. 航空兵器, 2019, 26(1): 83-88.WANG Z, HAN B L. An intelligent recognition method for jamming target based on UKF track filtering[J]. Aero Weaponry, 2019, 26(1): 83-88. (in Chinese)[10］钱杏芳, 林瑞雄, 赵亚男, 等. 导弹飞行力学[M]. 北京: 北京理工大学出版社, 2012: 31-36.QIAN X F, LIN R X, ZHAO Y N, et al. Missile flight aerodynamics[M]. Beijing: Beijing Institute of Technology Press, 2012: 31-36. (in Chinese)[11］ VO B N, MA W K. The Gaussian mixture probability hypothesis density filter[J].IEEE Transactions on Single Processing, 2006, 54(11): 4091-4104.[12］李云湘. 基于PHD滤波的多目标跟踪技术研究[D]. 长沙: 国防科学技术大学, 2012.LI Y X. Research on the multi-target tracking techniques based on probability hypothesis density filter[D]. Changsha: National University of Defense Technology, 2012. (in Chinese)[13］顾海燕, 罗双才. 波门拖引干扰类型识别方法研究[J]. 电子信息对抗技术, 2010, 25(6): 45-49.GU H Y, LUO S C. Arecognition approach of gate-pull jamming[J]. Electronic Information Warfare Technology, 2010, 25(6):45-49.(in Chinese)[14］ FREDRIK G, GUSTAF H. Some relations between extended and unscented Kalman filters[J]. IEEE Transactions on Signal Processing, 2012, 60(2):545-555.

[1]	梁苑，戚国庆，陈烨，李银伢，盛安冬. 不完全量测下事件触发水面扩展目标跟踪[J]. 兵工学报, 2024, 45(4): 1219-1228.
[2]	宋晓茹, 刘康, 高嵩, 陈超波, 阎坤. 复杂战场环境下改进YOLOv5军事目标识别算法研究[J]. 兵工学报, 2024, 45(3): 934-947.
[3]	熊光明, 罗震, 孙冬, 陶俊峰, 唐泽月, 吴超. 基于红外相机和毫米波雷达融合的烟雾遮挡无人驾驶车辆目标检测与跟踪[J]. 兵工学报, 2024, 45(3): 893-906.
[4]	金秋延, 刘福祥, 王新春, 刘晓, 莫波. 滚仰式导引头斜置方案下的过顶奇异问题控制策略[J]. 兵工学报, 2024, 45(2): 628-640.
[5]	杨家铭, 潘悦, 王强, 曹怀刚, 高荪培. 水下弱目标跟踪的深度学习方法研究[J]. 兵工学报, 2024, 45(2): 385-394.
[6]	马潇, 李新祺, 刘镇源, 邸超. 基于背景感知相关滤波跟踪器的目标快速跟踪方法[J]. 兵工学报, 2024, 45(2): 497-503.
[7]	赵军民, 何浩哲, 王少奇, 聂聪, 焦迎杰. 复杂环境下多无人机目标跟踪与避障联合航迹规划[J]. 兵工学报, 2023, 44(9): 2685-2696.
[8]	赵晓冬, 张洵颖. 基于YOLOv5的无人车自主目标识别优化算法[J]. 兵工学报, 2023, 44(9): 2732-2744.
[9]	刘冰, 郝新红, 周文, 杨瑾. 基于BAS-BPNN的调频无线电引信目标与扫频干扰识别方法[J]. 兵工学报, 2023, 44(8): 2391-2403.
[10]	郑磊, 陈志敏, 贾宇轩. 基于广域部署智能反射面的无人机集群跟踪方法[J]. 兵工学报, 2023, 44(6): 1837-1845.
[11]	刘灿, 王辉, 林德福, 崔晓曦, 徐晗晖. 存在非高斯重尾分布噪声的纯方位目标跟踪算法[J]. 兵工学报, 2023, 44(5): 1469-1481.
[12]	郑泽新, 李伟, 邹鲲, 李艳福. 基于强化学习的对空雷达抗干扰波形设计[J]. 兵工学报, 2023, 44(5): 1422-1430.
[13]	霍健, 陈慧敏, 马云飞, 郭鹏宇, 杨旭, 孟祥盛. 基于MEMS激光雷达的车辆目标识别算法[J]. 兵工学报, 2023, 44(4): 940-948.
[14]	赵飞, 娄文忠, 冯恒振, 苏子龙, 汪金奎, 宣炜琨. 反无人机图像导引头远距空中目标探测技术[J]. 兵工学报, 2023, 44(4): 1023-1033.
[15]	李国飞, 汤清璞, 吴云洁. 从飞行器无导引头的主-从式多飞行器协同制导方法[J]. 兵工学报, 2023, 44(11): 3436-3446.