Aircraft trajectory planning for improving vision-based target geolocation performance

Abstract

A method of improving the location accuracy of a target when imaged from an unmanned aerial vehicle (UAV) is described. This method focuses on improving estimation of heading angle bias to then improve geolocation performance. A Particle Swarm Optimization (PSO) algorithm is employed to derive an expression of optimal flight path, which can be a guide for trajectory planning. The aircraft is commanded to fly in the expected path generated by trajectory planning for taking 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 demonstrated by simulation results.