基于单站无源运动定位的多目标跟踪方法

doi:10.12305/j.issn.1001-506X.2025.08.13

系统工程与电子技术 ›› 2025, Vol. 47 ›› Issue (8): 2549-2557.doi: 10.12305/j.issn.1001-506X.2025.08.13

• 传感器与信号处理 • 上一篇

基于单站无源运动定位的多目标跟踪方法

马晓萌¹^,²(), 邓东明²^,*(), 沈永健²(), 丁金闪¹(), 郝国卿²()

1. 西安电子科技大学电子工程学院，陕西西安 710071
2. 北京遥测技术研究所，北京 100094

收稿日期:2024-05-06 出版日期:2025-08-25 发布日期:2025-09-04
通讯作者: 邓东明 E-mail:mxm_201359@163.com;dengdongming19@163.com;shenyongshen@163.com;ding@xidian.edu.cn;13994552790@163.com
作者简介:马晓萌（1989—），女，高级工程师，博士研究生，主要研究方向为雷达信号处理、阵列信号处理
沈永健（1985—），男，研究员，博士，主要研究方向为电子侦察与对抗系统设计
丁金闪（1980—），男，教授，博士，主要研究方向为新体制雷达系统设计、信号处理
郝国卿（1998—），男，工程师，硕士，主要研究方向为阵列信号处理、雷达信号处理
基金资助:
国家自然科学基金（62171358）资助课题

Multi-target tracking method based on single observer passive motion location

Xiaomeng MA¹^,²(), Dongming DENG²^,*(), Yongjian SHEN²(), Jinshan DING¹(), Guoqing HAO²()

1. School of Electronic Engineering，Xidian University，Xi’an 710071，China
2. Beijing Research Institute of Telemetry，Beijing 100094，China

Received:2024-05-06 Online:2025-08-25 Published:2025-09-04
Contact: Dongming DENG E-mail:mxm_201359@163.com;dengdongming19@163.com;shenyongshen@163.com;ding@xidian.edu.cn;13994552790@163.com

摘要/Abstract

摘要：

针对单站无源运动定位中的多目标定位问题，基于随机有限集（random finite set，RFS）的高斯混合多目标滤波器（Gaussian mixture multi-target filter，GM-MTF）提出一种多目标单站无源运动定位方法。首先，基于单站无源运动定位方法，将定位问题等效为目标跟踪问题，同时构建无源定位体系下的多目标跟踪非线性量测模型。其次，基于GM-MTF，给出融合容积卡尔曼滤波器的高斯混合实现过程以适应量测非线性模型，并给出完整的实现过程。在此基础上，联合相位差变化率定位法提出一种二次滤波的单站无源多目标定位方法。所提方法通过将单站无源运动定位和RFS多目标滤波器进行融合，将单目标定位场景进一步拓展到复杂的多目标场景。同时，通过仿真结果表明，对比传统的相位差变化率定位法，所提方法不仅定位精度优势明显，而且在复杂的杂波环境下具备一定的抗干扰能力和鲁棒性。

关键词: 单站无源运动定位, 多目标跟踪, 高斯混合, 有限集统计, 容积卡尔曼滤波

Abstract:

To address the multi-target localization problem in single observer passive motion localization, a multi-target single observer passive motion localization method is proposed based on the Gaussian mixture multi-target filter （GM-MTF） of the random finite set （RFS）. Firstly, based on the single observer passive motion location method, the localization problem is equivalent to a target tracking problem, and the nonlinear measurement model of multi-target tracking in the passive location system is constructed. Then, based on the GM-MTF, a Gaussian mixture implementation process fused with the cubature Kalman filter is provided to adapt to the measurement nonlinearity model, and the complete implementation process is given. On this basis, combined with the phase difference change rate positioning method, a single observer passive multi-target positioning method with secondary filtering is proposed. The proposed method integrates single observer passive motion localization and RFS multi-target filters, thereby further expanding the single target localization scene to complex multi-target scenes. Meanwhile, simulation results show that compared with traditional phase difference rate of change positioning methods, the proposed method not only has significant advantages in positioning accuracy, but also has certain anti-interference ability and robustness in complex clutter environments.

Key words: single observer passive motion location, multi-target tracking, Gaussian mixture, finite set statistics, cubature Kalman filtering （CKF）

中图分类号:

TP 274

马晓萌, 邓东明, 沈永健, 丁金闪, 郝国卿. 基于单站无源运动定位的多目标跟踪方法[J]. 系统工程与电子技术, 2025, 47(8): 2549-2557.

Xiaomeng MA, Dongming DENG, Yongjian SHEN, Jinshan DING, Guoqing HAO. Multi-target tracking method based on single observer passive motion location[J]. Systems Engineering and Electronics, 2025, 47(8): 2549-2557.

图/表 13

表1

图1

图2

图3

表2

图4

图5

图6

图7

图8

图9

图10

图11

参考文献 35

1	田中成, 刘聪锋. 无源定位技术[M]. 北京: 国防工业出版社, 2015: 374−379.
	TIAN Z C, LIU C F. Passive location technology[M]. Beijing: National Defense Industry Press, 2015: 374−379.
2	GHOLAMI M R, GEZICI S, STROM E G. A concave-convex procedure for TDOA based positioning[J]. IEEE Communications Letters, 2013, 17 (4): 765- 768. doi: 10.1109/LCOMM.2013.020513.122732
3	LI W C, WEI P, XIAO X C. A robust TDOA-based location method and its performance analysis[J]. Science in China Series F: Information Sciences, 2009, 52 (5): 876- 882. doi: 10.1007/s11432-009-0101-1
4	WU G Z, GUO F C, ZHANG M. Direct position determination: an overview[J]. Journal of Radars, 2020, 9 (6): 998- 1013.
5	孙仲康, 郭福成, 冯道旺. 单站无源定位跟踪技术[M]. 北京: 国防工业出版社, 2008: 5−6.
	SUN Z K, GUO F C, FENG D W. Passive location and tracking technology by single observer[M]. Beijing: National Defense Industry Press, 2008: 5−6.
6	CHEN Y T, TOWERS J J. Sequential localization of a radiating source by Dopple-shifted frequency measurements[J]. IEEE Trans. on Aerospace and Electronic Systems, 1992, 28 (4): 1084- 1089. doi: 10.1109/7.165370
7	HUANG H, ZHE0NG Y R. Node location with AOA assistance in multi-hop underwater sensor networks[J]. Ad Hoc Networks, 2018, 78, 32- 41. doi: 10.1016/j.adhoc.2018.05.005
8	ZHENG Q, CHEN J Q, YANG R J. Research on technology based on orthogonal multi-station angle measurement method[J]. Infrared Physics & Technology, 2017, 86, 202- 206.
9	许耀伟, 孙仲康. 利用相位差变化率对固定辐射源的无源被动定位[J]. 系统工程与电子技术, 1999, 21 (3): 34- 37.
	XU Y W, SUN Z K. Passive location of fixed emitter using phase rate of change[J]. Systems Engineering and Electronics, 1999, 21 (3): 34- 37.
10	周丹丹. 基于相位差变化率的单星无源定位方法研究[D]. 西安: 西安电子科技大学, 2023.
	ZHOU D D. Research on single star passive location method based on phase difference change rate[D]. Xi’an: Xidian University, 2023.
11	相飞华. 固定单站对机载辐射源目标高精度定位算法研究[D]. 长沙: 国防科技大学, 2022.
	XIANG F H. Research on high precision location algorithm for airborne emitter target with fixed single observer[D]. Changsha: National University of Defense Technology, 2022.
12	招乾民. 单星无源定位跟踪技术研究[D]. 成都: 电子科技大学, 2024.
	ZHAO Q M. Research on single satellite passive localization and tracking technology[D]. Chengdu: University of Electronic Science and Technology of China, 2024.
13	李永生, 董光焰, 陈凯, 等. 基于卡尔曼滤波的无源定位精度分析[J]. 弹箭与制导学报, 2022, 42 (4): 44- 46.
	LI J S, DONG G Y, CHEN K, et al. Accuracy analysis of passive location based on Kalman filter[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2022, 42 (4): 44- 46.
14	XU J, HE M, YU C L, et al. A new method of fixed single observer passive location based on phase difference rate-of-change[C]//Proc. of the 3rd International Conference on Measuring Technology and Mechatronics Automation, 2011: 174−177.
15	ANDERSON B D O, MOORE J B, ESLAMI M. Optimal filtering[J]. IEEE Trans. on Systems Man & Cybernetics, 2007, 12(2): 235−236.
16	JULIER S, UHLMANN J, DURRANT- WHYTE H F. A new method for the nonlinear transformation of means and covariances in filters and estimators[J]. IEEE Trans. on Automatic Control, 2000, 45 (3): 477- 482. doi: 10.1109/9.847726
17	ARASARATNAM I, HAYKIN S. Cubature Kalman filters[J]. IEEE Trans. on Automatic Control, 2009, 54 (6): 1254- 1269. doi: 10.1109/TAC.2009.2019800
18	QIU Z B, GUO L. Improved cubature Kalman filter for spacecraft attitude estimation[J]. IEEE Trans. on Instrumentation and Measurement, 2021, 70, 9504213.
19	单月晖, 赵巨波, 孙仲康. MGEKF算法在无源定位中的应用[J]. 航天电子对抗, 2003, (1): 10- 13.
	SHAN Y H, ZHAO J B, SUN Z K. Application of MGEKF algorithm in passive location[J]. Aerospace Electronic Warfare, 2003, (1): 10- 13.
20	郭福成, 李宗华, 孙仲康. 无源定位跟踪中修正协方差扩展卡尔曼滤波算法[J]. 电子与信息学报, 2004, 26 (6): 917- 922.
	GUO F C, LI Z H, SUN Z K. The modified covariance extended Kalman filtering passive location and tracking[J]. Journal of Electronics & Information Technology, 2004, 26 (6): 917- 922.
21	MAHLER R P S. Statistical multi-source multi-target information fusion[M]. Norwood: Artech House, 2007.
22	MAHLER R P S. Advances in statistical multi-source multi-target information fusion[M]. Norwood: Artech House, 2014.
23	MAHLER R P S. Multitarget Bayes filtering via first-order multitarget moments[J]. IEEE Trans. on Aerospace and Electronic Systems, 2003, 39 (4): 1152- 1178. doi: 10.1109/TAES.2003.1261119
24	MAHLER R P S. PHD filters of higher order in target number[J]. IEEE Trans. on Aerospace and Electronic Systems, 2007, 43 (4): 1523- 1543. doi: 10.1109/TAES.2007.4441756
25	VO B N, MA W K. The Gaussian mixture probability hypothesis density filter[J]. IEEE Trans. on Signal Processing, 2006, 54 (11): 4091- 4104. doi: 10.1109/TSP.2006.881190
26	VO B N, SINGH S, DOUCET A. Sequential Monte Carlo methods for multitarget filtering with random finite sets[J]. IEEE Trans. on Aerospace and Electronic Systems, 2005, 41 (4): 1224- 1245. doi: 10.1109/TAES.2005.1561884
27	VO B N, VO B T, HOANG H G. An efficient implementation of the generalized labeled multi-Bernoulli filter[J]. IEEE Trans. on Signal Processing, 2017, 65 (8): 1975- 1987. doi: 10.1109/TSP.2016.2641392
28	VO B T, VO B N, CANTONIA. The cardinality balanced multi-target multi-Bernoulli filter and its implementations[J]. IEEE Trans. on Signal Processing, 2009, 57 (2): 409- 423. doi: 10.1109/TSP.2008.2007924
29	VO B N, VO B T, PHUNG D. Labeled random finite sets and the Bayes multi-target tracking filter[J]. IEEE Trans. on Signal Processing, 2014, 62 (24): 6554- 6567. doi: 10.1109/TSP.2014.2364014
30	YI W, JIANG M, HOSEINNEZHAD R. The multiple model Vo-Vo filter[J]. IEEE Trans. on Aerospace and Electronic Systems, 2017, 53 (2): 1045- 1054. doi: 10.1109/TAES.2017.2667300
31	LI S Q, YI W, HOSEINNEZHAD R. Multi-object tracking for generic observation model using labeled random finite sets[J]. IEEE Trans. on Signal Processing, 2018, 66 (2): 1045- 1054.
32	CHEN Y, SHENG X L, GUO L X, et al. Asynchronous multisonar data integration approach used to detect sparse targets[J]. IEEE Acess, 2019, 7, 37908- 37917. doi: 10.1109/ACCESS.2019.2906327
33	杨威, 付耀文, 龙建乾, 等. 基于有限集统计学理论的目标跟踪技术研究综述[J]. 电子学报, 2012, 40 (7): 1440- 1448.
	YANG W, FU Y W, LONG J Q, et al. The FISST-based target tracking techniques: a survey[J]. Acta Electronica Sinica, 2012, 40 (7): 1440- 1448.
34	SCHUHMACHER D, VO B T, VO B N. A consistent metric for performance evaluation of multi-object filters[J]. IEEE Trans. on Signal Processing, 2008, 56 (8): 3447- 3457. doi: 10.1109/TSP.2008.920469
35	LI X R, JILKOV V P. Survey of maneuvering target tracking. Part I: dynamic models[J]. IEEE Trans. on Aerospace and Electronic Systems, 2004, 39 (4): 1333- 1364.

定位方法	定位精度	定位速度	航迹要求	目标定位	实现难度
测向交叉法	较慢	高	低	好	容易
多普勒频率法	快	较快	低	一般	较难
到达时间法	较慢	较快	高	一般	容易
多普勒频率变化率法	快	高	高	一般	一般
相位差变化率定位法	快	较高	低	一般	容易

目标	新生时刻/s	消亡时刻/s	初始位置/m	速度/（m/s）
目标1	1	60	[900,800]	[−4.3,4]
目标2	1	60	[800,900]	[−4.3,4]
目标3	1	60	[500,450]	[−4.3,4]

[1]	张洪源, 龚柏春, 韩飞, 孙玥, 宁昕. 复杂环境下天基无源协同多目标初始定轨方法[J]. 系统工程与电子技术, 2025, 47(5): 1404-1413.
[2]	郭泽坤, 杨洪飞, 刘峥, 谢荣, 冉磊, 李嘉楠. 基于MGMD空间的窄带雷达空中目标识别方法[J]. 系统工程与电子技术, 2025, 47(4): 1136-1145.
[3]	潘超凡, 李润生, 胡庆, 包全福, 保永强. 基于惯性预测的遥感场景舰船多目标跟踪模型[J]. 系统工程与电子技术, 2025, 47(1): 41-51.
[4]	单靖原, 卢雨, 凌寒羽. 鲁棒自适应的机载外辐射源雷达多目标跟踪算法[J]. 系统工程与电子技术, 2024, 46(9): 2902-2915.
[5]	江林海, 龚柏春, 刘传凯, YANG Yang, 张仁勇. 天基分布式无源探测的空间多目标跟踪方法[J]. 系统工程与电子技术, 2024, 46(8): 2789-2797.
[6]	姚思亦, 李万春, 高林, 张花国, 胡航玮. 基于分布式PMHT的多传感器多目标跟踪[J]. 系统工程与电子技术, 2024, 46(7): 2184-2190.
[7]	卓娅玲, 李响, 左磊, 胡娟. 随机数据丢包情况下组网雷达功率分配算法[J]. 系统工程与电子技术, 2024, 46(6): 1957-1966.
[8]	齐美彬, 庄硕, 胡晶晶, 杨艳芳, 胡元奎. 基于联合GLMB滤波器的可分辨群目标跟踪[J]. 系统工程与电子技术, 2024, 46(4): 1212-1219.
[9]	曾舒雅, 饶彬. 基于动力学守恒定律的弹道目标关联方法[J]. 系统工程与电子技术, 2024, 46(2): 684-691.
[10]	王希彬, 戴洪德, 全闻捷, 王瑞, 贾临生. 基于加速度补偿的惯性行人导航非零速区间姿态估计CKF算法[J]. 系统工程与电子技术, 2023, 45(9): 2894-2901.
[11]	毕文豪, 周杰, 张安, 刘力. 杂波环境下基于最大熵模糊聚类的JPDA算法[J]. 系统工程与电子技术, 2023, 45(7): 1920-1927.
[12]	刘政玮, 陈映, 鲁耀兵. 适用于多目标轨迹小角度交叉的PHD滤波器[J]. 系统工程与电子技术, 2023, 45(4): 982-990.
[13]	柳子然, 戴梓健, 岳程斐, 王培基, 曹喜滨. 基于高斯混合过程的空间机器人任务空间预测控制方法[J]. 系统工程与电子技术, 2023, 45(11): 3597-3605.
[14]	安雷, 李召瑞, 吉兵. 杂波环境下可移动主被动传感器长时调度方法[J]. 系统工程与电子技术, 2023, 45(1): 165-174.
[15]	穆静, 严东升, 蔡远利, 王长元. 基于Masreliez-Martin的鲁棒分数阶容积卡尔曼滤波算法及应用[J]. 系统工程与电子技术, 2023, 45(1): 234-240.

基于单站无源运动定位的多目标跟踪方法

Multi-target tracking method based on single observer passive motion location

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

图/表 13

参考文献 35

相关文章 15

编辑推荐

Metrics

本文评价