Attack-resilient Estimation for Linear Discrete-time Stochastic Systems with Input and State Constraints

In this paper, an attack-resilient estimation algorithm is presented for linear discrete-time stochastic systems with state and input constraints. It is shown that the state estimation errors of the proposed estimation algorithm are practically exponentially stable.