Trajectory Planning for Improving Vision-Based Target Geolocation Performance Using a Quad-Rotor UAV

This paper describes a novel method to improve the target location accuracy through imaging it from an aircraft. This method focuses on improving estimation accuracy of heading angle bias and then to improve geolocation performance. A particle swarm optimization algorithm is employed to derive an expression of optimal trajectory, which can be a guide for trajectory planning. Thanks to the maneuverability of quad-rotor unmanned aerial vehicles, the aircraft is commanded to follow path generated by trajectory planning to acquire multiple bearing measurements of the ground object. The main result is that the aircraft's heading angle bias can be more accurately estimated using trajectory planning. Hence, the target is more accurately geolocated. The efficacy of this technique is verified and demonstrated by simulation results and flight test.