Random Sets in Data Fusion: A New Framework for Multitarget Tracking

Abstract

Although a connection between multitarget tracking and random set theory was recognized during the course of development of the indirect-estimation tracking algorithms, it was only recently that such a connection started to be discussed based on random set theory. In this paper, the limitation of the traditional multitarget tracking framework was discussed, firstly, which separates tracking system into several estimation subproblems to solve respectively, and then, the early-stage direct-estimation tracking approach affinitive with random set theory is summarized. Ultimately this paper presents random set direct-estimation framework of a general theory of multitarget tracking which overcome the limitation of the traditional framework. Under this new framework, recent developments of the random set tracking techniques is discussed, in an attempt to explore further applications of random set theory to data fusion.