基于箱粒子的ET-CBMeMBer滤波算法  

CBMeMBer Filter for Extended Target Tracking Using Box Particle

作　　者：刘艳君[1] 刘祖鹏 LIU Yan-jun LIU Zu-peng(School of Computer and Information Engineering, Xinxiang University, Xinxiang 453003, China Department of Electronics and Communication Engineering, Henan Institute of Technology, Xinxiang 453000, China)

机构地区：[1]新乡学院计算机与信息工程学院,河南新乡453003 [2]河南工学院电子通信工程系,河南新乡453000

出　　处：《电光与控制》2017年第8期56-60,共5页Electronics Optics & Control

基　　金：河南省高等学校重点科研项目(14A510025;17B510001)

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.

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 

分 类 号：O213.2[理学—概率论与数理统计]