Persistent automatic tracking of multiple surface vessels by fusing radar and lidar

This paper addresses the problem of automatic target tracking of multiple surface vessels for unmanned surface vehicles (USVs). For safe USV operation, the detection of vessels in the surrounding environment is an important capability, and marine radars have been used to detect and estimate their motion. However, vessel detection at short-range using radars is challenging due to their inherent shadow zone. Therefore, we proposes a vessel tracking approach fusing a pulse radar and a 3D lidar. The relative bearing and range information between a USV and nearby vessels is obtained using radar and lidar sensors, and their motion including the position, heading, and speed is estimated based on a dual filter structure using an extended Kalman filter (EKF). This approach enables persistent tracking of multiple surface vessels. To verify and demonstrate the feasibility of the proposed method, a field experiment was performed in an inland river environment and the results are presented.