in: Advances in Estimation, Navigation, and Spacecraft Control, Daniel Choukroun,Yaakov Oshman,Julie Thienel,Moshe Idan, Editor, Springer, London/Berlin , Berlin, pp.391-411, 2015
In case of normal operational conditions for a satellite, a conventional
Kalman Filter gives sufficiently good attitude estimation results. On
the other hand, when there is a fault in the measurements then the
Kalman filter fails about providing the required accuracy and may even
collapse by time. In this paper, a Robust Kalman filtering method is
proposed for the attitude estimation problem. By using the proposed
method both the Extended Kalman Filter and Unscented Kalman Filter are
modified and the new algorithms, which are robust against the
measurement malfunctions, are called as the Robust Extended Kalman
Filter (REKF) and Robust Unscented Kalman Filter (RUKF), respectively.
The adaptation is performed following both single and multiple scale
factor based schemes. As an application example the proposed algorithms
are applied for attitude estimation of a small satellite and the
performance of the robust Kalman filters are compared in case of
different measurement faults.