Adaptive Huber{Based Filtering Using Projection Statistics: Application to Spacecraft Attitude Estimation

This paper discusses the development of an adaptive discrete-time robust flltering technique. The technique is based on a recursive form of Huber’s mixed minimum ‘1/‘2 norm approach to estimation, which is robust with respect to deviations from the assumed Gaussian error probability distributions inherent to the Kalman fllter. An adaptive scheme is proposed whereby the fllter can estimate the process noise and measurement noise covariance matrices along with the state estimate and state estimate error covariance matrix. The adaptation technique also adopts a robust approach to estimating these covariances that can resist the efiects of outliers. The adaptive/robust fllter is applied to the spacecraft attitude quaternion estimation problem, using a standard multiplicative approach for handling the quaternion norm constraint. Simulation cases involving both Gaussian and non-Gaussian error distributions are provided.