Robust target localization and tracking using Kalman filtering for UGV-UAV coordinated operation

Abstract

The need of robust target tracking and localization in UGV-UAV coordinated operation is the most important. Common target localization and tracking techniques that are widely adopted in practice are either utilizing wide area surveillance using unmanned aerial vehicle (UAV) sensors and providing crucial information to on-ground unmanned ground vehicle (UGV). The limitations of existing techniques are inaccurate target localization and tracking due to inaccessible target position. This paper considers the problem of cooperative target tracking with UAV subject to indirect measurement of target position using sensors on UAV. In this paper, it is demonstrated that better tracking results are obtained by using Kalman filtering, under noisy and unpredictable target observation scenario. The accuracy of target tracking depends on measurement of GPS sensor data from UAV & UGV. By performing several experiments tracking accuracy up to approx. 20m has been achieved.