Vision-based navigation for autonomous space rendezvous with non-cooperative targets

This study addresses the issue of vision-based navigation for space rendezvous with non-cooperative targets. After a brief description of the scenario and its peculiarities, the theory underlying monocular edges-based tracking for pose estimation is recalled and an innovative tracking algorithm is formally developed and implemented. This algorithm is coupled with a dynamic Kalman Filter propagating the dynamics which underlies a space rendezvous. The navigation filter increases the robustness of target position and attitude estimation, and allows the estimation of target translational velocity and rotation rate using only pose measurements. Moreover, the filter implements a computationally efficient delay management technique that allows merging the delayed and infrequent measurements typical of vision-based navigation. The performance of the algorithm is tested in different scenarios with high fidelity synthetic images.