基于TPHD与TCPHD滤波器的分布式多目标跟踪方法

doi:10.12305/j.issn.1001-506X.2025.09.06

系统工程与电子技术 ›› 2025, Vol. 47 ›› Issue (9): 2828-2838.doi: 10.12305/j.issn.1001-506X.2025.09.06

• 电子技术 • 上一篇

基于TPHD与TCPHD滤波器的分布式多目标跟踪方法

傅嘉政¹^,²(), 郭玉霞¹^,², 张博祥³, 柴雷³, 易伟³^,*, 孔令讲³

1. 中国空空导弹研究院，河南洛阳 471009
2. 空基信息感知与融合全国重点实验室，河南洛阳 471009
3. 电子科技大学信息与通信工程学院，四川成都 611731

收稿日期:2024-02-02 出版日期:2025-09-25 发布日期:2025-09-16
通讯作者: 易伟 E-mail:cn_FJZ_fea@outlook.com
作者简介:傅嘉政（1998—），男，助理工程师，硕士，主要研究方向为分布式多传感器多目标跟踪
郭玉霞（1979—），女，研究员，硕士，主要研究方向为雷达系统总体设计
张博祥（1995—），男，博士研究生，主要研究方向为多目标跟踪
柴　雷（1995—），男，博士研究生，主要研究方向为多目标跟踪、多传感器信息融合
孔令讲（1974—），男，教授，博士研究生导师，博士，主要研究方向为雷达信号处理、新体制雷达、统计信号处理

Distributed multi-target tracking method based on TPHD and TCPHD filters

Jiazheng FU¹^,²(), Yuxia GUO¹^,², Boxiang ZHANG³, Lei CHAI³, Wei YI³^,*, Lingjiang KONG³

1. China Airborne Missile Academy，Luoyang 471009，China
2. National Key Laboratory of Air-based Information Perception and Fusion，Luoyang 471009，China
3. School of Information and Communication Engineering，University of Electronic Science and Technology of China，Chengdu 611731，China

Received:2024-02-02 Online:2025-09-25 Published:2025-09-16
Contact: Wei YI E-mail:cn_FJZ_fea@outlook.com

摘要/Abstract

摘要：

在航迹随机有限集的分布式多目标跟踪方法中，同一目标在不同传感器下估计航迹可能出现起始时间或航迹长度不一致的问题，提出一种基于航迹状态空间结构（state space structure，SSS）的分布式跟踪方法以及该方法的高斯混合模型实现。在基于加权算术平均融合准则的分布式多目标跟踪框架下，结合航迹概率假设密度滤波器与航迹基数概率假设密度滤波器，利用航迹SSS信息，将航迹随机有限集的信息融合问题分治为多个独立的单一线性空间内子随机有限集信息融合问题。仿真实验基于广义最优子模式匹配度量方法比较了该方法与多种跟踪方法的跟踪性能，该方法估计结果与真实航迹误差最小，表明了该方法的有效性。

关键词: 分布式多目标跟踪, 航迹随机有限集, 加权算术平均融合, 航迹概率假设密度滤波器, 航迹基数概率假设密度滤波器

Abstract:

In distributed multi-target tracking methods based on trajectory random finite set （RFS）, the initiation time or the trajectory length of the trajectory estimate for the same target may be inconsistent across different sensors, and a distributed tracking method based on trajectory state space structure （SSS） is proposed with Gaussian mixture model implementation.In the distributed multi-target tracking framework based on the weighted arithmetic average （WAA） fusion criterion, combining the trajectory probability hypothesis density （TPHD） filter and the trajectory cardinality probability hypothesis density （TCPHD） filter, the information fusion problem of the trajectory RFS is divided into multiple independent sub RFS information fusion problems in a single linear space using the trajectory SSS information. Experiments are conducted to compare the tracking performance of this method with various tracking methods by generalized optimal subpattern assignment metric. This method produced estimates with minimal error compared to the actual trajectories, demonstrating the effectiveness of the algorithm.

Key words: distributed multi-target tracking, trajectory random finite set, weighted arithmetic average fusion, trajectory probability hypothesis density （TPHD） filter, trajectory cardinality probability hypothesis density （TCPHD） filter

中图分类号:

TJ 670
TN 95

傅嘉政, 郭玉霞, 张博祥, 柴雷, 易伟, 孔令讲. 基于TPHD与TCPHD滤波器的分布式多目标跟踪方法[J]. 系统工程与电子技术, 2025, 47(9): 2828-2838.

Jiazheng FU, Yuxia GUO, Boxiang ZHANG, Lei CHAI, Wei YI, Lingjiang KONG. Distributed multi-target tracking method based on TPHD and TCPHD filters[J]. Systems Engineering and Electronics, 2025, 47(9): 2828-2838.

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算法	多目标跟踪	剪枝合并	状态估计提取	WAA融合
SSS-WAA-TPHD	3.42e-2	2.71e-3	3.00e-3	8.61e-3
SSS-WAA-TCPHD	4.15e-2	2.78e-3	3.02e-3	8.71e-3

基于TPHD与TCPHD滤波器的分布式多目标跟踪方法

Distributed multi-target tracking method based on TPHD and TCPHD filters

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