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

Abstract

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

CLC Number:

TJ 670
TN 95

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.

Figures/Tables 8

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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

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

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