A Far Range Image Processing Method for Autonomous Tracking of an Uncooperative Target
This paper proposes an image processing method for far range rendezvous. A target spacecraft at distances up to $30$~km is tracked from camera images. The method is based on linking bright, connected sets of pixels over sequences of images. Stars and the target spacecraft are identified by using a star catalog and performing motion segmentation. The algorithm is illustrated in detail and 
%the visibility of stars and of the target are analyzed which is a prerequisite to perform far range image processing. Further, 
results of a flight experiment called ARGON are presented. The experiment took place in the extended phase of the PRISMA mission. The image processing method was employed and a successful rendezvous from $30$~km to $3$~km was accomplished using optical navigation.
Flight Demonstration of Non-Cooperative Rendezvous using Optical Navigation
The ultimate goal of this work is to demonstrate the capability of a maneuverable servicer spacecraft to rendezvous with a non-cooperative space resident object from far-range distance using optical angles-only measurements. To this end, the Advanced Rendezvous experiment using GPS and Optical Navigation (ARGON) has been executed during the extended phase of the PRISMA formation-flying mission in April 2012. This paper addresses the experiment design, the developed flight dynamics system, the obtained flight results, and the lessons learned. Furthermore the evaluation of the rendezvous tracking, navigation and control accuracy is performed by means of GPS-based precise relative orbit determination products. The presented results give a clear demonstration of the high readiness level reached by key technologies which are needed by future on-orbit servicing and debris-removal missions.
Real-Time Vision-Based Relative Navigation
This paper describes two vision-based techniques for the navigation of an aircraft relative to an airborne target using only information from a single camera fixed to the aircraft. By applying an Extended Kalman Filter (EKF) for relative state estimation, both the velocity and position of the aircraft relative to the target can be estimated. While relative states such as bearing can be estimated fairly easily, estimating the range to the target is more difficult because it requires achieving valid depth perception with a single camera. The two techniques presented here offer distinct solutions to this problem. The first technique, Center Only Relative State Estimation (CORSE), uses optimal control to generate an optimal (sinusoidal) trajectory to a desired location relative to the target that results in accurate range-to-target estimates while making minimal demands on the image processing system. The second technique, Subtended Angle Relative State Estimation (SARSE), uses more rigorous image processing to arrive at a valid range estimate without requiring the aircraft to follow a prescribed path. Simulation results indicate that both methods yield range estimates of comparable accuracy while placing different demands on the aircraft and its systems.