Sensor Resource Mgmt Using a Genetic Algorithm Appoarch

"Missile defense is moving toward a 'system of systems' approach, and the level of autonomy within individual sensing components becomes more challenging. The battle management segment must manage the available sensor resources for engagement planning andutilization of interceptor inventories. Battle management tasking is more goal-oriented forcing the sensors to determine the best approach for meeting mission goals. A sophisticated sensor management processing scheme, which performs high-level intelligentresource scheduling based on genetic algorithms (GA) is proposed. The sensor management process determines a viable solution for scheduling resources, including specifying parameters for the sensor activities of surveillance, search, track, anddiscrimination. These activities are scheduled in accordance within the sensor constraints and limits. The GA is a population-based model using selection and recombination operators to generate new sample points. The GA challenge is generating an encodingscheme that represents the possible scheduling solutions into the chromosome-like structures, and utilizing the recombining and mutating operators. This project proposes developing the encoding scheme representing the scheduling solution typified by asensor performing the fire-control functionality needed for defending against ICBM threats. Future efforts will generalize the approach for other assets such as overhead surveillance and seeker sen