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 paper 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 paper are applied to the problem of tracking a ground vehicle on the special Euclidean group SE(2).
翻译:综合概率数据协会过滤器(IPDAF)是一种基于概率数据协会过滤器的目标跟踪算法,该算法计算出一种统计计量,表明目标的估计表示是否正确代表目标,或来自非目标的测量结果。本文的主要贡献是使综合概率数据协会能够适应在连接的、单一的谎言组上演进的持续速度目标模型,而且测量结果也是在一个谎言组上定义的。我们举了一个例子,说明如何将文件中制定的方法应用于跟踪欧洲精密分子特别组SE(2)的地面车辆。