机动目标概率假设密度滤波算法及其比较*

刘枫; 吴小俊

doi:10.15892/j.cnki.djzdxb.2011.03.014

弹箭与制导学报 >

2011 , Vol. 31 >Issue 3: 53 - 55,62

DOI: https://doi.org/10.15892/j.cnki.djzdxb.2011.03.014

导弹与制导技术

机动目标概率假设密度滤波算法及其比较*

刘枫 ,
吴小俊

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江南大学信息工程学院,江苏无锡 214122

刘枫(1986-),男,江苏扬州人,硕士研究生,研究方向:计算机软件与理论。

收稿日期: 2010-08-05

网络出版日期: 2025-05-30

基金资助

教育部新世纪优秀人才计划(NCET-60-0467);国家自然科学基金(60572034,60973094);江苏省自然科学基金(BK2006081);江南大学创新团队研究计划(JWIRT0702)资助

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Maneuvering Target Tracking with Probability Hypothesis Density Filter Algorithm and Its Comparability

LIU Feng ,
WU Xiaojun

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School of Information Engineering, Jiangnan University, Jiangsu Wuxi 214122, China

Received date: 2010-08-05

Online published: 2025-05-30

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摘要

在多目标跟踪问题中,如果目标数未知或者随着时间的变化而变化,那么联合概率数据关联(JPDA)等一系列在目标数已知时使用的跟踪算法就难以应对,而概率假设密度(PHD)滤波算法将目标集合数看成一个随机集,避免了数据关联问题。文中将PHD算法与JPDA算法进行了比较,仿真实验结果表明:在杂波环境下,PHD算法对目标数未知或随时间变化的多目标跟踪情况良好,在相同仿真条件下,PHD算法在时间上花的代价比其他算法更少。

关键词： 多目标跟踪; 概率假设密度; 随机集; 联合概率数据关联

本文引用格式

刘枫 , 吴小俊 . 机动目标概率假设密度滤波算法及其比较*[J]. 弹箭与制导学报, 2011 , 31(3) : 53 -55,62 . DOI: 10.15892/j.cnki.djzdxb.2011.03.014

Abstract

In multi-target tracking problem, if the number of targets is unknown or varies with time, the tracking algorithms' applications in identified target including joint probabilistic data association (JPDA) become difficult to deal with, but the target set is taken as a random set by probability hypothesis density (PHD), thus data association is avoided. In this article, the PHD was compared with the JPDA. The simulation results show that PHD algorithm can be used to track a changing number of targets in clutter, and is much less than other algorithm in the time complexity in the same simulation.

Key words： multi-target tracking; probability hypothesis density; random sets; joint probabilistic data association

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