Direct data fusion using the PMHT

Abstract

We analyze the tracking characteristics of a new data-association/tracking algorithm proposed by Streit-Luginbuhl, the probabilistic multi-hypothesis tracking (PMHT) algorithm, in a multisensor environment. Given that in the formulation of the algorithm there is no constraint on the number of measurements originated per target, it is a natural candidate for direct fusion in the multi-sensor case, where a combined frame (assuming synchronicity among the sensors) may have more than one target-originated measurement. In this paper we compare the performance of this new algorithm to that of a commonly used multisensor tracking algorithm: the joint probabilistic data association filter with a centralized estimation-to-estimation fusion.