The Probabilistic Multi-Hypothesis Tracker (PMHT) is an emerging algorithm that has shown some success and is
intriguing because of its elegance and extensibility in many different aspects. It is a tracking algorithm that offers an
alternative to the Multiple Hypothesis Tracker (MHT) in the multiple-frame tracking arena. Instead of enumerating
many of the possibilities of track-to-measurement assignments, the PMHT uses a probabilistic approach to assign
the likely "weight" of each measurement to contribute to each track. This paper presents the ongoing results of
research using the 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.