现代防御技术2025，Vol.53Issue(1)：23-36,14.DOI:10.3969/j.issn.1009-086x.2025.01.003
基于信息关联加权的多目标跟踪算法
Multi-target Tracking Algorithm Based on Information Association and Weighting
摘要
Abstract
A probability hypothesis density filtering algorithm based on information association weighting is proposed to address the two issues of decreased accuracy in multi-target state estimation and overestimation of the number of multi-targets,which are caused by asynchronicity and high-density clutter aliasing in passive and active radar detection information across multiple platforms.Firstly,a multi-target tracking model is constructed,and the mechanism of why existing algorithms are susceptible to clutter is analyzed.Secondly,a multi-target tracking algorithm based on information association weighting is derived.The tolerance time parameter is set according to the target speed and tolerable error,and the detection information with a short asynchronous time is approximated as synchronous information.The association algorithm is used to select passive and active radar information from the same target,and the minimum variance weighted fusion is used to improve detection accuracy.The randomly distributed clutter is filtered out,due to its association difficulties caused by large differences in angle values.Finally,simulation analysis shows that the proposed algorithm improves the accuracy of multi-target state estimation and reduces the overestimation of the number of multi-targets compared to existing algorithms.关键词
多目标跟踪/协同探测/概率假设密度滤波/信息关联/最小方差加权Key words
multi-target tracking/cooperative detection/probability hypothesis density(PHD)/information association/minimum variance weighting分类
军事科技引用本文复制引用
于勇政,王伟,蒲治伟..基于信息关联加权的多目标跟踪算法[J].现代防御技术,2025,53(1):23-36,14.基金项目
国家自然科学基金(62271163) （62271163）
