Study of Multi-target Tracking and Data Association Based on Sequential Monte Carlo Algorithm

Fan Lin-bo, K. Li, Wu Ying-cheng, Zhao Ming
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引用次数: 3

Abstract

A new method based on sequential Monte Carlo algorithm is proposed for tracking multi-target and data association in non-linear system. The algorithm partitions the problem of multi-target tracking into two problems: single target tracking and data association. Single target tracking is implemented by using UKF and data association by using sequential Monte Carlo algorithm. Since Particle Filter has advantages in non-linear non-Gauss system, the proposed method performs well in the experiment.
基于顺序蒙特卡罗算法的多目标跟踪与数据关联研究
提出了一种基于时序蒙特卡罗算法的非线性系统多目标跟踪和数据关联的新方法。该算法将多目标跟踪问题划分为单目标跟踪和数据关联两个问题。采用UKF实现单目标跟踪,采用时序蒙特卡罗算法实现数据关联。由于粒子滤波在非线性非高斯系统中具有优势,该方法在实验中取得了良好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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