基于LMB滤波的分布式多传感器多目标跟踪

doi:10.12305/j.issn.1001-506X.2026.06.12

Abstract

Abstract:

The multi-sensor multi-target fusion tracking method based on label multi-Bernoulli （LMB） posterior density has problems, such as label inconsistency, high miss-detection and track switches, and poor continuity. To address this problem, a distributed multi-sensor multi-target tracking method is developed based on LMB posterior trajectory estimation. Firstly, the objective function is established to minimize the multi-frame state difference and time dimension correlation switches between tracks estimated by different sensors. The convex relaxation technique is used to simplify the high-dimensional nonlinear objective function into a linear form, and the effective correlation of tracks is achieved in polynomial time through clustering and linear programming. Then, the generalized covariance intersection criterion and complementarity principle are used to fuse correlated trajectories in parallel. Finally, a fusion method for un-correlated trajectories is derived based on finite set statistics. Simulation experiments show that the proposed method effectively improves trajectory continuity and reduces trajectory missed-detections and switches, verifying its fine engineering application value.

Key words: label random finite set, tracks correlation, convex relaxation, generalized covariance intersection

CLC Number:

TN 957

Zhiwei WANG, Xingyu CAI, Wei XU, Chao YAN. Distributed multi-sensor multi-target tracking based on LMB filter[J]. Systems Engineering and Electronics, 2026, 48(6): 1905-1912.

Figures/Tables 9

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融合方法	检测概率	总体误差	位置误差	漏检航迹	错误航迹	跳变航迹	融合时间/s
LF-GCI-LMB	0.75	39.05	23.99	24.30	13.68	0.2365	115.34
LM-GCI-LMB	0.75	39.25	22.67	29.54	4.80	0.0581	20.05
MFJO-GCI-TLMB	0.75	33.37	23.61	18.88	5.35	0.0358	19.21

Distributed multi-sensor multi-target tracking based on LMB filter

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