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.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.