White noise filters for systems with multiple packet dropouts

This paper is concerned with the optimal white noise estimation problem for linear discrete-time stochastic systems with multiple packet dropouts. Based on the optimal linear state predictor, the optimal linear white noise filters for the input white noise and measurement white noise are developed in the linear minimum variance sense via the innovation analysis approach. When there are packet dropouts, the white noise filtering algorithms in the previous literatures under complete measurement data have lost the optimality. A numerical example is given to demonstrate the effectiveness of the proposed algorithm.