The Integrated Probabilistic Data Association Filter Adapted to Lie Groups
The Integrated Probabilistic Data Association Filter Adapted to Lie Groups
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DOI：
10.1109/taes.2022.3214803
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发表时间：
2021-08
影响因子：
4.4
通讯作者：
Mark E. Petersen;R. Beard
中科院分区：
文献类型：
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作者：
Mark E. Petersen;R. Beard
集成概率数据关联滤波器（iPad）是基于概率数据关联滤波器的目标跟踪算法，其计算指示目标的估计表示是否正确地表示目标或从非目标起源的测量生成的统计测量。这篇文章的主要贡献是使IPv6适应于在连通的单模李群上演化的等速目标模型，并且测量也在李群上定义。我们提出了一个例子，在文章中开发的方法被应用到跟踪地面车辆的问题上的特殊欧几里德群SE（2）。
The integrated probabilistic data association filter (IPDAF) is a target tracking algorithm based on the probabilistic data association filter that calculates a statistical measure that indicates if an estimated representation of the target properly represents the target or is generated from non-target-originated measurements. The main contribution of this article is to adapt the IPDAF to constant velocity target models that evolve on connected, unimodular Lie groups, and where the measurements are also defined on a Lie group. We present an example where the methods developed in the article are applied to the problem of tracking a ground vehicle on the special Euclidean group SE(2).