A robust navigation filter fusing delayed measurements from multiple sensors and its application to spacecraft rendezvous

Abstract

A filter is an essential part of many control systems. For example guidance, navigation and control systems for spacecraft rendezvous require a robust navigation filter that generates estimates of the state in a smooth and stable way. This is important for a safe spacecraft navigation within rendezvous missions. Delayed, asynchronous measurements from possibly different sensors require a new filter technique which can handle these different challenges. A new method is developed which is based on an Extended Kalman Filter with several adaptations in the prediction and correction step. Two key aspects are extrapolation of delayed measurements and sensor fusion in the filter correction. The new filter technique is applied on different close-range rendezvous examples and tested at the hardware-in-the-loop facility EPOS 2.0 (European Proximity Operations Simulator) with two different rendezvous sensors. Even with realistic delays by using an ARM-based on-board computer in the hardware-in-the-loop tests the filter is able to provide accurate, stable and smooth state estimates in all test scenarios.