H∞ fusion estimation for sensor network systems under DoS attacks

Sensor network systems are essential for numerous technological applications. However, the vulnerability to cyber threats can severely affect both performance and security of the systems. The problem of H∞ fusion estimation is explored for sensor network systems under the influence of Denial-of-Service (DoS) attacks. To address this problem, a Luenberger-type local state estimator is specifically designed to compensates for sensor data affected by DoS attacks using the estimated data. These estimations are subsequently forwarded to a fusion center for comprehensive analysis and processing, with the aim of improving the reliability and precision of the sensor networks systems. By use of Lyapunov stability analysis, the sufficient conditions are established to ensure the boundedness of fused estimation errors and H∞ performance. The required gains for the local estimator and fusion weight matrices are determined by solving a series of linear matrix inequalities, which guarantees the stability and convergence of the fusion estimation systems. Finally, the effectiveness of the proposed fusion scheme are authenticated via simulation experiments.