Autonomous detection and tracking of a surface ship using onboard monocular vision

This study addresses autonomous detection and tracking of a surface ship using a monocular camera mounted on an unmanned surface vehicle (USV). Automatic feature extraction and tracking filter algorithms are used for vision-based detection and tracking in real-time. For target tracking, the bearing and range to the target ship with respect to the own ship are obtained by computer vision techniques. The pixel distance from the horizon to the target in camera images is used to extract the range information, and a probing maneuver procedure is designed to enhance observability of the target tracking filter. The feasibility and performance of the proposed tracking approach are validated through field experiments with two USVs.