Event-Triggered Dsitributed State Estimation with Innovation Saturation for Discrete Time-Delayed Networked Systems Subject to Deception Attacks

This article proposes a design of event-triggered distributed estimator with innovation saturation for a specific class of systems with distributed time delays in sensor networks. The sensors measure the system with distributed time delay and transmit the measurements to remote estimators for state estimation. The measurements sent by sensors will be injected with false signals which can be described by Bernoulli distribution. The remote estimators use the received measurements and the saturated innovation of the adjacency estimators to estimate the state of the system, which is transmitted under the event-triggering mechanism. By using the Lyapunov-Krasovskii functional, a series of sufficient conditions are proposed to ensure that the error system is mean-square bounded. Furthermore, the gains of the distributed estimators are obtained by solving the LMIs. Finally, a numerical example is presented to verify the effectiveness of the proposed design.