SVD-Aided EKF with process noise covariance adaptation applied to satellite attitude dynamics

An attitude estimation scheme is designed with the process noise adaptation rule in the extended Kalman filter (EKF) algorithm for a spacecraft in low Earth orbit. The adaptations are designed for compensating the external disturbances by updating the process noise covariance. Satellite attitude estimation algorithm based on the Singular Value Decomposition (SVD) as a preprocessing step in EKF is proposed. The process noise covariance (Q) adaptation rule is incorporated into the previous filter design. The proposed filter has the capability to be robust against initialization errors and the dynamics modeling errors of the satellite. Numerical simulations based on several scenarios are employed to investigate the robustness of the filter.