Abstract
This paper presents a newly developed algorithm for multitarget tracking using multipattern data association. Multipattern data association is based on a novel approach for tracking multiple targets using multiple patterns extracted from measurement sequences. A Markov chain controls the switching behavior of multipatterns, which allows an interacting operation of multipatterns. The introduction of patterns leads to a new paradigm of developing high-performance algorithms. A powerful tracking algorithm – interacting multipattern joint probabilistic data association (IMP-JPDA) is developed. The IMP-JPDA algorithm can be considered as a generalized joint probabilistic data association (JPDA) algorithm; when only one scan of measurements is used, IMP-JPDA reduces to JPDA.
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