一种新的基于概率理论的概率数据互联滤波器

刘宗香; 谢维信; 黄敬雄

doi:10.3724/SP.J.1146.2008.00796

一种新的基于概率理论的概率数据互联滤波器

doi: 10.3724/SP.J.1146.2008.00796

基金项目:

国家部级基金和深圳大学科研启动基金(200640)资助课题

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出版历程
- 收稿日期: 2008-06-23
- 修回日期: 2009-03-23
- 刊出日期: 2009-07-19

A New Probabilistic Data Association Filter Based on Probability Theory

摘要

摘要: 该文从理论上分析了用于目标跟踪的概率数据互联滤波器(PDAF)和联合概率数据互联滤波器(JPDAF)存在的不足，提出了一种新的概率数据互联滤波器(NPDAF)。NPDAF在数据关联时基于概率理论：一个测量可能源于目标，也可能源于杂波，但其源于目标的概率与其源于杂波的概率之和应为1。同时，给出了跟踪过程中NPDAF的数据互联模型及滤波器的实现方法。该实现方法首先计算测量与各目标的关联概率，然后用概率对跟踪滤波器的增益加以修正。仿真实验表明，在对多目标进行跟踪时NPDAF的性能优于JPDAF。
- 目标跟踪;概率理论;概率数据互联滤波器;联合概率数据互联滤波器
Abstract: The Probabilistic Data Association Filter (PDAF) and the Joint Probabilistic Data Association Filter (JPDAF) are theoretically analyzed and their shortages in theory are pointed out. Based on the probability theory, a New Probabilistic Data Association Filter (NPDAF) is proposed, in which a measurement may originate from targets or a clutter, but the sum of the probabilities originating from targets and a clutter is equal to 1. Also in the paper, the mathematical model for data association in target tracking and the realization technique for NPDAF are presented. The　correlative probabilities between a measurement and targets are first computed in the realization technique, then the gain of a tracking filter is modified using the correlative probability. Simulation results show that the performance of NPDAF is better than that of JPDAF in multiple target tracking.

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