In this article, we consider the Kalman filter (KF)-based state estimation in the multisensor
networked control systems. The sensors communicate plant state observations to a remote …

We consider a fundamental remote state estimation problem of discrete-time linear time-
invariant (LTI) systems. A smart sensor forwards its local state estimate to a remote estimator …

We study a networked state estimation problem for a linear system with multiple sensors,
each of which transmits its measurements to a central estimator via a lossy communication …

We investigate the stability conditions for remote state estimation of multiple linear time-
invariant (LTI) systems over multiple wireless time-varying communication channels. We …

This work studies the state estimation problem of a networked linear system where a sensor
and an estimator are connected via a lossy network. If the measurement loss is known to the …

This paper studies the remote Kalman filtering problem for a distributed system setting with
multiple sensors that are located at different physical locations. Each sensor encapsulates …

We consider the problem of state estimation over lossy networks. Although a large number
of approaches have been proposed to improve the estimator's performance, most of them …

Challenges associated with the scarcity of bandwidth and power in wireless
communications have to be addressed. For the state-estimation problems discussed in the …

This article discusses the remote state estimation over unreliable links, where the packet
dropouts occur from the sensor side to the filter, for discrete-time systems with both bounded …

Distributed Kalman filter (DKF) is an effective method to solve the problem of state estimation
in multi-sensor systems. However, the accuracy of conventional DKF may be influenced by …