Robust decentralised state estimation for formation flying spacecraft

Abstract

In this study, a robust decentralised state estimation algorithm named decentralised Huber-based cubature filtering (DHCF) for formation flying spacecraft is proposed. In this algorithm, a decentralised architecture is designed, in which each deputy estimates its relative state with respect to the chief based on its own exteroceptive sensor measurement. The relative motion equation considering the non-spherical influence of the earth is derived. The relative measurements' information contain not only the line-of-sight between the deputy and the chief, but also the ranges among the deputies, which improves the redundancy of the relative navigation task. A set of cubature points are selected using spherical-radial rule to map the probability distribution, which is more accurate than the linearisation of the extended Kalman filter (EKF). The non-Gaussian noise in formation is approximated by Gaussian mixture models. To deal with the non-Gaussian noise, the Huber technique is used in measurement update of each deputy and the extra measurement uncertainty caused by linearisation is compensated. Simulation results indicate that the proposed DHCF provides better performance in state estimation accuracy and robustness when compared to decentralised EKF and decentralised cubature Kalman filtering in the presence of non-Gaussian measurement noise.