Huber Second-order Variable Structure Predictive Filter for Satellites Attitude Estimation

This work presents a novel filtering approach to the high-accuracy attitude estimation problem of satellites. A new second-order variable structure predictive filter is first designed with the measurement errors and their difference reduced. The key feature of this filter is that the noise handled is not constrained to be the Gaussian white noise. Hence, it is a new solution to filtering problem in the presence of modeling errors or heavy-tailed noise. Then, the robust version of the preceding filter is developed by using the Huber technique. This robust filter can ensure great robustness and perfect estimation accuracy/precision for the satellite attitude. The Lyapunov stability analysis proves that the measurement error and its difference can be stabilized into a small set with a faster rate of convergence. The effectiveness of the presented attitude estimation filters is validated via simulation by comparing with the traditional cubature Kalman filter.