Vision-Based Tracking of Uncooperative Targets

Abstract

This paper presents a summary of a subset of the extensive vision-based tracking methods developed at Georgia Tech. The problem of a follower aircraft tracking an uncooperative leader, using vision information only, is addressed. In all the results presented, a single monocular camera is used as the sole source of information used to maintain formation with the leader. A Kalman filter formulation is provided for the case where image processing may be used to estimate leader motion in the image plane. An additional piece of information, the subtended angle, also available from computer vision algorithm is used to improve range estimation accuracy. In situations where subtended angle information is not available, an optimal trajectory is generated that improves range estimation accuracy. Finally, assumptions on the target acceleration are relaxed by augmenting a Kalman Filter with an adaptive element.