Covariance intersection based event-triggered distributed state estimation under channel independent DoS attacks

This paper investigates the event-triggered distributed state estimation problem for a class of discrete time-varying systems in the presence of denial-of-service (DoS) attacks, where each sensor node selectively shares its local information with neighbors. In contrast to the previous studies where the DoS attacks are considered on sensor-to-filter channels, we deal with the situation that DoS attacks jam each filter-to-filter communication channel independently. To reduce the communication rate and save network resources, a novel event-triggered communication strategy is presented that takes into account the impact of DoS attacks and is specialized for each communication channel. Based on the covariance intersection fusion rule and weight rearrangement method, a distributed state estimation algorithm is proposed. Further, the consistency of estimates and mean-square boundedness of estimation errors are proved under system collective observability and some other mild assumptions. Lastly, a numerical simulation is conducted to demonstrate the developed results and the effectiveness of the proposed algorithm.