On multitarget pairwise-Markov models, II

被引：2

作者：

Mahler, Ronald ^{[1
]}

机构：

[1] Random Sets LLC, Eagan, MN 55121 USA

来源：

SIGNAL PROCESSING, SENSOR/INFORMATION FUSION, AND TARGET RECOGNITION XXVI | 2017年 / 10200卷

关键词：

Multitarget tracking; pairwise Markov chain; CPHD filter; random finite set; CHAINS;

D O I：

10.1117/12.2262787

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

This paper is the seventh in a series aimed at weakening the independence assumptions that are typically presumed in multitarget tracking. Two years ago at this conference, we initiated an exploratory analysis of general multitarget pairwise-Markov (MPMC) systems, which weaken the multitarget Markov assumption. Based on this analysis, we derived an exploratory CPHD filter for MPMC systems. Unfortunately, this approach relied on heuristic models in order to incorporate both spatial and cardinality correlation between states and measurements. This paper describes a fully rigorous approach provided, however, that only cardinality correlation is taken into account. We derive the time-update and measurement-update equations for a CPHD filter describing the evolution of such an MPMC system.

引用

页数：12