Optimal UAV Sensor Management and Path Planning for Tracking Multiple Mobile Targets

In this paper, we present an optimal sensor manager and a path planner for an Unmanned Aerial Vehicle (UAV) to geo-localize multiple mobile ground targets. A gimbaled camera with a limited field of view (FOV) and a limited range is used to capture targets, whose states are estimated using a set of Extended Kalman Filters (EKFs). The sensor management is performed using a dynamic weighted graph and a Model Predictive Control (MPC) technique, determining the optimal gimbal pose that minimizes the overall uncertainty of target states. A UAV path planner that maximizes a novel cost function is employed to support the sensor management. Simulation results show the effectiveness of the proposed sensor manager and the path planner.