Dual Intensity Filter for Reciprocal Awareness of Clutter & Targets (DIFFRACT)

Target tracking for multi-static sonar systems is inherently a low signal-to-noise ratio (SNR), multi-sensor, and multi-target problem. Tracker designs for multi-static sonar systems have previously focused on the low SNR and multi-sensor aspect of the problem. With advances in applying random finite set theory to tracking, along with increases in computational power, it is now possible to incorporate the multi-target nature of the multi-static air anti-submarine warfare (ASW) sonar tracking problem into the solution as well. Probability Hypothesis Density filtering will be used for track initiation and track maintenance and will jointly estimate target and clutter intensity. Multiple Hypothesis Tracking will be used for track state estimation and association. This approach allows for the use of the strong points of each algorithm to create a tracker which can better achieve performance necessary for the warfighter than either technology alone.