Distributed state estimation for sensor networks with randomly occurring sensor saturations

This paper is concerned with the problem of distributed state estimation for a class of sensor networks characterized by the discrete-time dynamical systems. The discrete-time model with mixed time delays is used to express the target system. Outputs of the sensors are measured under randomly occurring saturations caused by physical restrictions of the sensors. By utilizing output measurements from each individual sensor and its neighboring sensors, we design distributed state estimators with a view to approximating the states of the target system in a distributed manner. Moreover, we show that the estimation error systems are globally asymptotically stable in the mean square, and also provide the explicit expressions of the distributed estimator gains.