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.

中文翻译：

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欺骗攻击下具有类死区审查的状态饱和系统的基于协议的融合估计器设计


本文关注一类受到类似死区审查和欺骗攻击的状态饱和系统的基于协议的融合估计问题。为了抑制数据冲突并减轻共享网络的通信开销，在传感器到过滤器通道上实施加权尝试一次丢弃协议，以按照规定的动态传输顺序协调多个传感器。伯努利分布随机变量用于描述潜在对手发起的欺骗攻击。利用著名的 Tobit 模型来描述类似死区的审查现象，其中审查区域受到某些左右审查阈值的限制。融合估计通过两个阶段实现：在第一阶段，每个传感器将其观测值发送到局部估计器，在第二阶段，然后将局部估计传输到融合中心以生成融合估计。局部估计器实现托比特卡尔曼滤波算法，从而保证一定的上限（局部滤波误差协方差），然后通过充分确定滤波器增益来最小化，而融合中心则通过联邦融合准则进行融合估计。此外，通过评估融合误差协方差上限的有界性来检查所设计的融合估计器的性能。最后通过数值例子证明了融合估计器的有效性。