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.

Time and Covariance Threshold Triggered Optimal Uncooperative Rendezvous Using Angles-Only Navigation

“…For these reasons, autonomous vehicles using AON are currently an active area of research [4][5][6][7][8][9][10][11][12][13][14]. The growing interest in vision-based autonomous rendezvous and docking has produced a series of experimental spacecraft in an attempt to develop rendezvous and proximity operations technology that would be 2 International Journal of Aerospace Engineering more appropriate for small satellite.…”

Case Study: Feasibility Analysis of Close-in Proximity Operations Using Angles-only Navigation

“…It is worth mentioning that using AON in autonomous vehicles is currently a hot research subject. [4][5][6][7][8][9][10][11][12][13][14] The growing interest in vision-based autonomous rendezvous and docking has not only resulted in the proposal of experimental satellite missions, but has also resulted in the development of close-rendezvous technology for small satellites. PRISMA 15) is the in-orbit test bed for AON technology.…”

Real Flight Application of a Monocular Image-Based Aircraft Collision Decision Method

“…However, in the case of small UAVs, the size, weight, and power consumption of the onboard S&A system should be minimal. Monocular vision-based solutions can be cost and weight effective and therefore especially good for small UAVs [9][10][11][12][13][14][15][16]. These systems measure the position (bearing) and size of the intruder aircraft (A/C) camera image without range and physical intruder size information.…”

“…This scale ambiguity makes the decision about the possibility of collision (collision means both mid-air collision or near mid-air collision in this article) complicated (see, e.g., [9] where a conservative assumption on intruder's minimum size is used to make the decision possible but this can lead to false alarms). In another source [13] where the task is to follow a leader aircraft based on a monocular camera, special maneuvers are required to provide range observability. However, [10] points out that the relative distance of the intruder from the own A/C called the closest point of approach (CPA) well characterizes the possibility of collision together with the time to closest point of approach (TTCPA) and there is a chance to estimate these parameters without any physical intruder information.…”

“…The only information lost is the absolute distance between the two A/C; the relative CPA values are determined instead, but this information is appropriate for the decision about the possibility of collision and for the design of an avoidance maneuver. SIL test results are presented, but in-flight testing of such methods is also very important as underlined by [4,13] for example.…”