Tracking multiple mobile targets using cooperative Unmanned Aerial Vehicles

In this paper, we present a decentralized cooperative multiple target tracking method for multiple Unmanned Aerial Vehicles (UAVs). The decentralized cooperative multi-target tracking algorithm incorporates an optimal sensor management scheme and a cooperative path planner. To localize and track targets, a set of Extended Kalman Filters (EKFs) is used onboard each UAV and resulting target estimates are shared among UAVs. The sensor management scheme determines optimal gimbal poses to track the maximum number of targets using a greedy algorithm and a path planner is used to coordinate desired trajectories of UAVs. The effectiveness of the proposed algorithm is demonstrated using simulation results.