文献类型：期刊文献

中文题名：基于箱粒子的ET-CBMeMBer滤波算法

英文题名：CBMeMBer Filter for Extended Target Tracking Using Box Particle

作者：刘艳君[1];刘祖鹏[2]

第一作者：刘艳君

机构：[1]新乡学院计算机与信息工程学院;[2]河南工学院电子通信工程系

第一机构：新乡学院计算机与信息工程学院

年份：2017

卷号：24

期号：8

起止页码：56-60

中文期刊名：电光与控制

外文期刊名：Electronics Optics & Control

收录：CSTPCD;;北大核心:【北大核心2014】；

基金：河南省高等学校重点科研项目(14A510025;17B510001)

语种：中文

中文关键词：目标跟踪算法;扩展目标;区间量测;CBMeMBer滤波;箱粒子滤波

外文关键词：target tracking algorithm ; extended target ; interval measurement ; CBMeMBer filter; box particle

摘要：为解决扩展目标跟踪算法量测不精确的问题,提出一种基于箱粒子滤波的ET-CBMeMBer滤波算法。该算法基于随机集理论,首先将扩展目标的状态集和观测集随机化,然后基于区间分析技术,推导了适用于区间量测的多扩展目标伪似然函数和势平衡多伯努利多扩展目标状态更新方程,并提出了适用于区间量测的模糊ART区间量测集划分方法,继而在量测集划分的基础上对目标进行持续稳定的跟踪。最后进行了仿真实验,结果表明了所提算法的有效性。
In order to solve the extended target tracking algorithm in the case of inaccurate measurement, an ET-CBMeMBer fiher algorithm based on box particle filter is proposed. Based on the stochastic set theory, the state set and the set of observations of the extended target are first randomized. Then, based on the interval analysis technique, the multi-extended target pseudo-likelihood function and the potential balance Bernoulli multi-extended target status updating function are deduced out. A fuzzy ART interval measurement set partitioning method suitable for interval measurement is proposed. Then, continuous and steady target tracking is implemented on the basis of the setting of measurement sets. Finally, the simulation experiment is carried out, and the results show the effectiveness of the proposed algorithm.