跟踪扩展目标——一种与SJPDAF相对的交换算法

A. Kräußling, D. Schulz
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引用次数: 7

摘要

跟踪扩展目标是移动机器人的核心兴趣,因为它是与环境交互的先决条件。点状目标跟踪与扩展目标跟踪存在显著差异。现有的算法大多假设目标是点状的,这并不总是适用的。近年来,作者提出了两种先进的扩展目标跟踪算法——切换算法和SJPDAF算法。切换算法使用卡尔曼滤波和一种改进版的维特比算法,其中包含了问题的某些几何特征。SJPDAF结合了粒子滤波与JPDAF的思想。本文给出了这两种算法,并对它们在交叉目标情况下的精度、速度和鲁棒性进行了比较。我们表明,最近开发的交换算法在这些标准方面优于SJPDAF
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Tracking Extended Targets - A Switching Algorithm Versus The SJPDAF
Tracking extended targets is of central interest in mobile robotics as it is a prerequisite for interaction with the environment. There are significant differences between tracking punctiform targets and tracking extended targets. Most of the existing algorithms assume the targets to be punctiform, which is not always suitable. In recent years, two advanced algorithms for tracking extended targets have been developed by the authors-a switching algorithm and the SJPDAF. The switching algorithm uses the Kalman filter and an adapted version of the Viterbi algorithm, which includes certain geometrical characteristics of the problem. The SJPDAF combines the idea of particle filtering with the JPDAF. In this paper we present these two algorithms and compare them with respect to accuracy, speed and robustness in case of crossing targets. We show, that the more recently developed switching algorithm outperforms the SJPDAF regarding these criterions
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