Optimized path planning for UAVS with AOA/scan based sensors

In emitter localization by unmanned aerial vehicles (UAVs) the objective of path planning is to determine the best UAV trajectories so as to maximize the instantaneous localization performance subject to various constraints. In this paper we propose gradient based waypoint update algorithms for UAVs equipped with angle-of-arrival (AOA) and scan based sensors. The optimization criterion used by the waypoint update algorithms is to maximize the determinant of the approximate Fisher information matrix. The effectiveness of the path planning algorithms is illustrated with several computer simulations.