Vision-Based Tracking of Uncooperative Targets

This paper presents a summary of a subset of the extensive vision-based tracking methods developedat Georgia Tech. The problem of a follower aircraft tracking an uncooperative leader, using visioninformation only, is addressed. In all the results presented, a single monocular camera is used as thesole source of information used to maintain formation with the leader. A Kalman filter formulationis provided for the case where image processing may be used to estimate leader motion in the imageplane. An additional piece of information, the subtended angle, also available from computer visionalgorithm is used to improve range estimation accuracy. In situations where subtended angle informationis 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 adaptiveelement