Real-time In-situ Adaptation of Decision Parameters for Undersea Target Tracking in a Sensor Field

Detection of moving targets in spatially-variable and uncertain environments is of prime importance in maritime intelligence, surveillance and reconnaissance (ISR) systems. However, the situational context may prohibit the placement of a single fixed long-term ISR system that can be fine-tuned to maximize performance in the area of interest. In such situations, distributed fields of passive sensor systems are often called for, as they allow the coverage of relatively large areas at a moderate cost. In this Phase II effort, the IAI and Penn State team will work in collaboration to achieve the following three objectives: 1) to develop algorithms that will improve the detection capability for sonar sensor networks as well as the models and algorithms for estimation of decision thresholds as needed for detection of moving targets in the undersea environment; 2) to develop a simulation and analysis capability that can be used to assess the merits of algorithms, networks, practices and equipment used in undersea sensor network operations; and 3) to demonstrate/evaluate the newly combined above technologies with use case scenarios. In particular, IAI will focus upon developing a reconfigurable and reusable simulation capability which Penn State will tailor to the specific problem of autonomous sensor search.