Advances in the PMHT as a network-level composite tracker

In 1995, Streit and Luginbuhl introduced a new tracking algorithm, which offered a balance between the single-frame approach of the probabilistic data association filter (PDAF) and the multiple frame approach of the multiple hypothesis trackers (MHT). With single-frame tracking algorithms, only information that has been received to date is used to determine the association between tracks and measurements. These decisions are made based on available data and are not changed even when future data may indicate that the decision was incorrect. On the other hand, in multi-frame algorithms, hard decisions are delayed until some time in the future, thus allowing the possibility that incorrect association decisions may be corrected with more data. This paper presents the ongoing results of research using the probabilistic multi-hypothesis tracker (PMHT) algorithm as a network-level composite tracker on distributed platforms. In addition, the methods necessary to implement the PMHT in a realistic simulation are discussed. It further describes the techniques that have been tried to ensure a single integrated air picture (SIAP) across the platforms