Sensor Networked Resilient Distributed State Estimation With Cyber Attacks: Theory and Application

In this article, a sensor networked resilient distributed estimation framework has been proposed, where intercommunication in the network is susceptible to cyber-attacks. Considering the uncertainty of the maneuvering characteristics of the target, an improved dynamic model is established for calculating the accurate local priori results by introducing a jerk component. Based on the consensus fusion protocol, the final estimation results are obtained after local neighboring interactions. To mitigate the impact of cyber-attacks on the intercommunication between neighboring nodes, the DoS-attacks are modeled with its average frequency and duration. In light of the target maneuvering model and DoS-attacks model, the resilient distributed algorithm is designed by local filtering, resilient, and consensus fusion stages. Additionally, the stability of the proposed resilient distributed estimation algorithm is analyzed with global observability. The simulation results demonstrate the performance of the proposed resilient algorithm. Furthermore, the cooperative equivalent experiment is conducted to validate the effectiveness of the proposed algorithm under DoS-attacks, which is consistent with the simulation results.