Abstract
This paper is concerned with the protocol-based fusion estimation problem for a class of state-saturated systems subject to dead-zone-like censoring and deception attacks. In order to curb data collisions and ease communication overheads of the shared networks, the weighted try-once-discard protocol is implemented on the sensor-to-filter channel to orchestrate multiple sensors with a prescribed dynamic transmission order. Bernoulli-distributed stochastic variables are utilized to characterize deception attacks initiated by potential adversaries. The well-known Tobit model is leveraged to characterize the dead-zone-like censoring phenomenon where censored regions are constrained by certain left- and right-censoring thresholds. The fusion estimation is implemented via two stages: at the first stage, each sensor sends its observations to the local estimator and, at the second stage, the local estimates are then transmitted to the fusion center so as to generate the fused estimate. The local estimators realize Tobit Kalman filtering algorithms such that certain upper bounds (on the local filtering error covariances) are guaranteed and then minimized via adequately determining filter gains, while the fusion center carries out the fusion estimation by resorting to the federated fusion criterion. Furthermore, the performance of the devised fusion estimator is examined through assessing the boundedness of the upper bound on the fused error covariance. The validity of the fusion estimator is finally shown via a numerical example.