Distributed multi-target tracking with labeled multi-Bernoulli filter considering efficient label matching  

作　　者：Changwen DING Chuntao SHAO Siteng ZHOUI Di ZHOU Runle DU Jiaqi LIU 

机构地区：[1]School of Astronautics,Harbin Institute of Technology,Harbin 150001,China [2]National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics,Beijing 100076,China

出　　处：《Frontiers of Information Technology & Electronic Engineering》2025年第3期400-414,共15页信息与电子工程前沿(英文版)

摘　　要：We propose a distributed labeled multi-Bernoulli(LMB)filter based on an efficient label matching method.Conventional distributed LMB filter fusion has the premise that the labels among local densities have already been matched.However,considering that the label space of each local posterior is independent,such a premise is not practical in many applications.To achieve distributed fusion practically,we propose an efficient label matching method derived from the divergence of arithmetic average(AA)mechanism,and subsequently label-wise LMB filter fusion is performed according to the matching results.Compared with existing label matching methods,this proposed method shows higher performance,especially in low detection probability scenarios.Moreover,to guarantee the consistency and completeness of the fusion outcome,the overall fusion procedure is designed into the following four stages:pre-fusion,label determination,posterior complement,and uniqueness check.The performance of the proposed label matching distributed LMB filter fusion is demonstrated in a challenging nonlinear bearings-only multi-target tracking(MTT)scenario.

关 键 词：Distributed multi-sensor multi-target tracking Labeled multi-Bernoulli filter Arithmetic average fusion Label matching 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]