In this paper, the advances of distributed fusion estimation (DFE) algorithms for multi-sensor
networked systems (NSs) are reviewed. First, several general DFE algorithms are reviewed …

This paper studies the distributed state estimation problem for a class of discrete time-
varying systems over sensor networks. Firstly, it is shown that the gain parameter …

State estimation problem for power systems has long been a fundamental issue that
demands a variety of methodologies depending on the system settings. With the recent …

This paper proposes a consensus Kalman filtering algorithm based on the leader–follower
structure and weighted average strategy for sensor networks. By introducing virtual …

This article investigates the distributed state estimation problem for large-scale power
systems with the appearance of bad data. The power system is decomposed into several …

Recent studies imply that despite having a high level of security features and accurate
algorithms, Phasor Measurement Units (PMUs) are vulnerable to False Data Injection (FDI) …

This article investigates the distributed state estimation problem for large-scale power
systems, where both false data injection (FDI) and denial-of-service (DoS) attacks are …

In this article, we address a partition‐based distributed state estimation problem for large‐
scale general nonlinear processes by proposing a Kalman‐based approach. First, we …

We study a distributed Kalman filtering problem in which a number of nodes cooperate
without central coordination to estimate a common state based on local measurements and …

This article proposes a data-driven distributed filtering method based on the consensus
protocol and information-weighted strategy for discrete-time sensor networks with switching …