Automatic target tracking with time-delayed measurements for unmanned surface vehicles

Abstract

This paper presents the automatic target detection and tracking of marine obstacles for unmanned surface vehicles (USVs). For practical applications with a USV, the automatic detection of surrounding obstacles is a crucial capability, and marine radars have been commonly used to detect and estimate the motion of obstacles. However, their tracking performance degrades when a target is approaching at a high relative velocity due to their relatively low sampling rate. This study addresses the automatic target tracking of marine obstacles by considering time-delayed measurements provided by a marine radar. The relative position information between a USV and nearby obstacles is obtained using the radar sensor, and the obstacles' motion including position, course, and speed is estimated using an extended Kalman filter (EKF)-based tracking filter by compensating the measurement delay. To validate the feasibility of the proposed method, a real-sea experiment was conducted using a USV and the results are presented. Copyright ？ 2019 SPIE.