Constrained Kalman filter for uncooperative spacecraft estimation by stereovision

In this paper a novel approach based on constrained extended Kalman filter is proposed for estimating the relative state of the uncooperative spacecraft. The approach uses information from the stereovision-based navigation system to provide multiple perspective projections of the feature points on the spacecraft. Specifically, the unobservability of the relative attitude and the feature points vectors is analyzed by means of Lie derivative in the spacecraft's system. Then, considering the unobservability, a physical constraint on the feature points vectors is embedded into the system and the system becomes observable. Furthermore, to improve the state estimation accuracy, the feature points positions are recovered from the projections and constitute the observation model of the filter. Consequently, the observation model is coupled with the constraint in an extended Kalman filter to determine the relative attitude and position. Finally, numerical simulations are conducted to validate the effectiveness of the proposed algorithm.