Optimal and suboptimal prior filters with bounded multiple packet dropouts

This paper is concerned with the filtering problem for discrete-time stochastic linear system with bounded multiple packet dropouts. An optimal prior filter is developed in linear unbiased minimum variance sense. Its solution depends on the recursion of a Riccati equation and a Lyapunov equation, which involves the complex computation of multiple sums by some correlated terms. To reduce the computational cost, a suboptimal prior filter is presented. Furthermore, the proposed optimal and suboptimal filters are reduced to the standard Kalman filters when there are no packet dropouts. A simulation shows the effectiveness of the proposed algorithms.