Search Optimization for Multiple Airborne and Air-Deployed Sensors using the Adaptive Simulated Annealing (ASA) Algorithm

The challenge presented in this SBIR topic is to create a tool that allows an operator to create near-optimal search plans for a given environment, suite of sensors and threat types. Sensor performance, often expressed in terms of a probability of detection, for each sensor type is predicted using the sensor's own tactical decision aid (TDA). This SBIR proposal does not recommend building additional TDAs for various sensors. The primary goals of the proposed work plan are the development of a technique to accurately sum the probabilities of detection from a heterogeneous set of sensors and the application of Adaptive Simulated Annealing (ASA) algorithm to solve the problem of determining near optimal search plans using a user selectable measure of effectiveness. A key strength of this approach is that it can be applied to both over-water and over-land searches. The approach uses the predictions of each sensor's TDA and therefore can be applied to both acoustic sensors and non-acoustic sensors (electromagnetic, electro-optic/infrared, radar and magnetic anomaly detection). The resulting product will generate near-optimal search plans to the mission planner for the predicted distribution of threats, the operating environment, suite of sensors available and user selected measure of effectiveness.