Acoustic Counterdetection Mitigation (ACDM) Decision Aid

In this SBIR project, Daniel H. Wagner Associates (DHWA) will develop Acoustic Counterdetection Mitigation (ACDM) Evolutionary Machine Learning (EML) algorithms and software, leveraging our existing Operational Route Planner (ORP), that will automatically produce a recommended, optimized ASW search that accurately computes cumulative counter-detection probability (CC-DP), accounts for the ability of threat submarines to react to counterdetections of friendly ASW assets, and will use multi-objective optimization techniques to provide multiple alternative, distinct, and non-dominated search plans to the Commander/search planner. ACDM will also explicitly account for the uncertainties in estimating threat counterdetection (and friendly search) effectiveness using our recently developed techniques for estimating probabilistic passive and active signal excess.