Single- and multi-platform constrained sensor path optimization for angle-of-arrival target tracking

This paper is concerned with optimal path planning for moving sensor platforms in angle-of-arrival (AOA) target tracking. A steering algorithm is developed to update sensor platform waypoints for a single or multiple AOA sensor platforms. The waypoint updates are derived from an iterative normalized gradient descent optimization algorithm subject to geometric and turn rate constraints. The sensor platform paths are optimized by minimizing a cost function comprising the mean-square error of predicted target position estimates produced by the extended Kalman filter and penalty functions for threat/obstacle avoidance. The effectiveness of the developed steering algorithm is illustrated with simulation examples.