Flight testing of a multiple UAV RF emission and vision based target localization method

In this paper, we present the flight tests of a solution for finding and localizing a radio frequency emitting target using multiple autonomous unmanned aerial vehicles. The method relies on Particle Filter and Extended Kalman Filter algorithms based on signal strength tracking. After estimation, vision-based detection is used in order to improve the localization. The proposed solution is first tested on an in-house developed software-in-the-loop system and then, radio frequency signal strength measurement tests and vision-based object detection tests are conducted in flight tests. Outdoor flight tests are performed and the results are presented with designed hardware and software architectures. The proposed solution meets of all operational requirements for the localization and the detection of the target.