Remote state estimation based on sensor networks
Z基于传感器网络的远程状态估计

A switched Kalman filter is proposed to realize the remote state-estimation in sensor networks. The stochastic properties of the estimation error are studied; and the covariance of the estimation error is proved to have bounds. Convergence conditions of the bounds are given in terms of linear matrix inequalities. The effects of packet-dropping are considered; and the critical arrival probability is used as the stability criterion of the estimator. The bounds of the critical arrival probability are obtained by using linear matrix inequality approach. The results are tested by numerical simulations.