Anti-Torpedo Data Fusion and Optimization System (ATDOS)

Daniel H. Wagner Associates, Inc. will develop a full-scale prototype Anti-Torpedo Data Fusion and Optimization System (ATDOS) which will fuse all available data using multiple hypothesis association, Gaussian sum and non-Gaussian tracking, Bayesian inferential reasoning and non-Gaussian registration techniques to produce a torpedo defense Tactical Picture (TP). Given this TP, ATDOS will optimize the utilization of all available anti-torpedo sensors, especially any active sensors, using non-Gaussian optimization algorithms. Although our initial focus will be on generating the torpedo defense TP and optimizing sensor utilization, in Phase III we may potentially optimize weapon employment as well. This use of advanced data fusion and optimization algorithms is critical for the success of an anti-torpedo system, since even the new passive and active sensors and their associated signal processing algorithms that are currently being developed will produce large numbers of both persistent false contacts (primarily from contacts on surface ships, although air targets could also be detected) and non-persistent false contacts. Thus it is critical to develop a sophisticated data fusion system that can process all of the available information concerning targets of interest, taking advantage of all of the detection and non-detection information produced by passive acoustic, active acoustic, and non-acoustic sensors.