Autonomous Environmental Sensor Performance Prediction Tool for Multi-Static Active and Passive Anti-Submarine Warfare (ASW) Systems

Current Air ASW sensor systems are complex in form and function with many operational settings as is the nature of the littoral and deep-water range- and time-dependent underwater acoustic environments in which the Navy applies them. Determining 3-dimensional sensor distributions and settings for optimal detection capability for an operational area and target of interest is difficult. Present modeling capabilities applied to sensor placement and setting optimization are necessarily constrained in spatial and temporal fidelity because of the curse of dimensionality: substantially more computing power is needed to calculate the best scenario from a full range of sensor settings and distributions over wide areas. A multi-stage, multi-threaded, distributed, and automated multi-static active and passive modeling and simulation capability is needed to help warfighters make decisions on where to fight, and once committed, make the best choice of sensor system to use (including distribution and settings) and provide feedback to improve coordination of future sorties based on in situ data. Innovative strategies employing alternative metrics to traditional probability of detection will be assessed for feasibility. Adaptive Methods and the Applied Physics Laboratory are well poised, based on previous work in this area, to bring forth this desired capability.