Observation-Trigger-Based Sequential Fusion Filter for CPSs with Correlated Noises and Multiplicative Noises Against Deception Attacks

In this paper, a sequential fusion time-varying estimator is presented to deal with the multiplicative noise, correlated noise and the uncertainty of deception attacks under observation-triggered mechanism. Firstly, the fictitious noise technique is applied to transform the uncertain cycle-physical systems (CPSs) into a standard state space model. In addition, the observationtriggered mechanism is introduced to fuse state estimation for selective triggering. Finally, the sequential matrix-weighted, sequential covariance intersection and sequential inverse covariance intersection fusion were carried out at the fusion center using the sequential structure to obtain the sequential fusion estimator. A simulation example of a CPS tracking system is used to verify the effectiveness of the results.