Robust information fusion filtering method for discrete-time linear uncertain system

The traditional Kalman filtering is difficult to obtain the accurate filtering results when applied in the system with existing modeling error and noise statistical uncertainty. Considering of this problem, a robust information fusion filtering method is proposed in this paper. Based on the measurement equation of the uncertain information, a robust information fusion estimation theorem is given and proved. For the discrete uncertain linear system, a robust information fusion filtering algorithm with easy calculation based on the theorem is deduced, the superiority of which is verified by the numerical simulation results, comparing with the traditional Kalman filtering method.