This paper presents a comparative analysis of performances of two types of multi-target tracking algorithms: 1)the Joint Probabilistic Data Association Filter (JPDAF), and 2) classical Kalman Filter based algorithms for multi-target tracking improved with Quality Assessment of Data Association (QADA) method using optimal data association. The evaluation is based on Monte Carlo simulations for difficult maneuvering multiple-target tracking (MTT) problems in clutter.
Comments: 8 Pages.
[v1] 2017-11-02 02:27:04
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