PMHT Track Fusion for ABIR

Fusing data together for target tracking is a complex problem. There are two elements: First, the raw observations must be associated with existing tracks or used to form new tracks. Once the association has been done, then the tracks can be updated and filtered with the new data. When associating data (either measurements or tracks or both) with existing tracks, the separation between the tracks is critical to how difficult the association decisions will be. If the tracks are widely separated then the association decisions can be relatively easy. On the other hand, when the tracks are closely spaced the association decisions can be very difficult or nearly impossible. At any rate, these and other concerns roil the current battle space for ballistic missile defense. This proposal will explore the fusing of ABIR data from a few sensors in order to provide to the C2BMC a reliable and consistent set of tracks. We are proposing to solve this problem by using a probabilistic Bayesian approach with the Probabilistic Multi-Hypothesis Tracker (PMHT). Using a probabilistic approach will mitigate the computation numerations that occur when there is significant uncertainty in association decisions.