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This paper presents a new robust filter structure to solve the simultaneous state and fault estimation problem of linearstochastic discrete-time systems with unknown disturbance. The method is based on the assumption that the fault and theunknown disturbance affect both the system state and the output, and no prior knowledge about their dynamical evolution isavailable. By making use of an optimal three-stage Kalman filtering method, an augmented fault and unknown disturbancemodels, an augmented robust three-stage Kalman filter (ARThSKF) is developed. The unbiasedness conditions and minimum-varianceproperty of the proposed filter are provided. An illustrative example is given to apply this filter and to compare itwith the existing literature results

Robust Filtering for State and Fault Estimation of Linear Stochastic Systems with Unknown Disturbance