计算机与数字工程2019，Vol.47Issue(2)：344-348,5.DOI:10.3969/j.issn.1672-9722.2019.02.018
边缘粒子滤波多目标跟踪改进算法研究
Improved Multitarget Tracking Algorithm Based on Marginalized Particle Filter
摘要
Abstract
In the process of multi-target tracking,a new algorithm based on edge particle filter is proposed to solve the prob?lem that the probability density filter does not estimate the number of targets and the state of target correctly. Application of Rao-Blackwellized algorithm,the target state is decomposed into linear and non-linear model structure. And RBPF filter prediction is used to predict and estimatethe non-linear stateof target,and Calman filtering method is used to predict and estimate the linear state,in order to improve the estimation accuracy of target state,and the complexity of calculation is reduced. Finally,the simula?tion experiments are carried out to verify the proposed algorithm. Compared with the existing algorithms,the proposed algorithm can estimate the number of targets and thestate of target more accurately,and has better tracking performance.关键词
粒子滤波/概率假设密度滤波/多目标跟踪Key words
particle filter/probability hypothesis density filter/multitarget tracking分类
信息技术与安全科学引用本文复制引用
石治国,吴铭,郝云鹏,施冬磊..边缘粒子滤波多目标跟踪改进算法研究[J].计算机与数字工程,2019,47(2):344-348,5.
