MS-KF fusion algorithm for drogue tracking

A mean shift-Kalman filter (MS-KF) fusion algorithm for drogue tracking in unmanned aerial vehicle (UAV) autonomous aerial refueling (AAR) was proposed. The drogue tracking theory based on mean shift (MS) algorithm, including drogue aim model, similarity measurement and drogue positioning, were analyzed. By introducing Kalman filter (KF), the drogue moving information was predicted and merged in MS algorithm in order to ensure the stability and robustness of the drogue tracking algorithm. The flow block diagram of drogue tracking based on MS-KF fusion algorithm was provided and the semiphysical experimental system of drogue tracking was constructed. The semi-physical verification experiment and numerical simulation analysis of MS-KF algorithm for drogue tracking were respectively conducted. Experimental results demonstrate that the MS-KF fusion algorithm can position and track drogue precisely and the tracking errors of the UAV axes keep within the range of 0.3m, which ensures the success of the UAV-AAR.