Multi-target Tracking and Recognition Technology Based on PHD and UKF

doi:10.3969/j.issn.1000-1093.2020.08.004

Abstract

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

CLC Number:

TJ765.3⁺31

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

References ［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]	LI Liangfu， CHEN Weidong， GAO Qiang， XU Kailuan， LIU Xuan， HE Xi， QIAN Jun. Deep Learning-based Intelligent Target Recognition Technology for Electro-optical System [J]. Acta Armamentarii, 2022, 43(S1): 162-168.
[2]	ZHANG Yunpu， SHAN Ganlin. Multi-sensor Cooperative Management for Ground Target Tracking under Road Constraints [J]. Acta Armamentarii, 2022, 43(3): 542-555.
[3]	ZHOU Jianping, LI Wei, WEN Qiuqiu, XIA Qunli, JIANG Huan. Stability Design of Spinning Missile Autopilot Considering Parasitical Loop of Roll-pitch Seeker [J]. Acta Armamentarii, 2022, 43(1): 1-10.
[4]	LI Jisan， HOU Jiao， LIU Rong， REN Yuan. Optimal Time Resource Allocation Algorithm for Surveillance Phased Array Radar Target Tracking Based on Bayesian FilteringAlgorithm [J]. Acta Armamentarii, 2021, 42(9): 1902-1910.
[5]	DING Haiting, ZHOU Lin, DIAO Weifeng. Knapsack Problem-based Algorithm for Time Resource Management of Multiple Phased Array Radars for Multiple Targets Tracking [J]. Acta Armamentarii, 2021, 42(5): 997-1003.
[6]	WANG Zhenfeng， LI Fei， WANG Xinyu， YANG Jiansen， QIN Yechen. State Estimation of Suspension System Based on Interacting Multiple Model Unscented Kalman Filter [J]. Acta Armamentarii, 2021, 42(2): 242-253.
[7]	ZHANG Junbiao， XIONG Jiajun， LAN Xuhui， LI Fan， CHEN Xin， XI Qiushi. Tracking Method for Hypersonic Glide Vehicle Based on Adaptive Multi-channel Interacting Multiple Model [J]. Acta Armamentarii, 2021, 42(12): 2626-2636.
[8]	CHEN Ke， ZHANG Yongfei， WANG Dulin， LIU Zijun， FU Xiaogang. Analysis of the Minor Deformation of Imaging Primary Mirror Supporting Platform of Missile at Low Temperature [J]. Acta Armamentarii, 2021, 42(12): 2637-2645.
[9]	XUE Lingzhi, ZENG Xiangyang, YANG Shuang. Underwater Acoustic Target Recognition Algorithm Based on Generative Adversarial Networks [J]. Acta Armamentarii, 2021, 42(11): 2444-2452.
[10]	WANG Jian， QIN Chunxia， YANG Ke， REN Ping. A SAR Target Recognition Algorithm Based on Guided Filter Reconstruction and Denoising Sparse Autoencoder [J]. Acta Armamentarii, 2020, 41(9): 1861-1870.
[11]	LU Liping, ZHENG Xiao. A Dynamic Target Tracking Method Based on Optical Imaging with Rotating Mirror [J]. Acta Armamentarii, 2020, 41(8): 1558-1565.
[12]	JIN Bingyang, LIU Zheng, QIN Jikai. Two-stage Real-time Track Correlation Algorithm Based on Gray Correlation [J]. Acta Armamentarii, 2020, 41(7): 1330-1338.
[13]	ZHANG Zheng， LIU Chunguang， MA Xiaojun， ZHANG Yunyin. Method for Estimating Sideslip Angle of All-wheel Drive Vehicle Based on Data Fusion [J]. Acta Armamentarii, 2020, 41(5): 842-849.
[14]	SHAO Pengfei, WANG Lei, WANG Fangyong. Active Distributed Sonar Multi-target Tracking Based on SMC-PHD Filtering [J]. Acta Armamentarii, 2020, 41(5): 941-949.
[15]	YU Honghai， YAN Xiaopeng， JIA Ruili， LI Ze， WANG Jiantao. Research on Anti-jamming Performance of M-sequence Pseudo-random Code Phase Modulation Pulse Doppler Fuze [J]. Acta Armamentarii, 2020, 41(3): 417-425.