Path Planning for UAV-Aided Wireless Positioning System Calibration

Autonomous placement of positioning beacons by an unmanned aerial vehicle (UAV) makes the establishment of wireless localization systems possible when manual placement is not a feasible option in GNSS-denied environments with potential risk. The UAV drops the beacons sequentially at designated horizontal locations, leading to an inaccurate estimate of the beacon positions. Therefore, UAV-aided calibration follows autonomous placement to establish a high-precision wireless positioning system by obtaining additional distance measurements from placed beacons. In this paper, we investigate the effect of the UAV’s path planning on the calibration result and focus on the waypoints that the UAV selects to make observations. We model the waypoint selection problem as an optimization problem based on Fisher information matrix (FIM) and solve it with quotient-space particle swarm optimization (PSO). The numerical results not only verify the efficiency of the quotient-space PSO in solving the optimization problem, but also show that the proposed method enables the movement of the UAV to introduce more distance measurements and significantly improve the accuracy of beacon positions, which in turn justifies the necessity of UAV’s path planning in assisting the calibration of wireless positioning systems.