One of the fundamental problems in sensor networks is to estimate and track the state of
targets (or dynamic processes) of interest that evolve in the sensing field. Kalman filtering …

Consensus-based algorithms for distributed Kalman filtering of the state of a dynamical
target agent have attracted considerable research and attention during the past decade. In …

The problem of distributed Kalman filtering (DKF) for sensor networks is one of the most
fundamental distributed estimation problems for scalable sensor fusion. This paper …

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

We consider the problem of decentralized Kalman filtering in a sensor network. Each sensor
node implements a local Kalman filter based on its own measurements and the information …

This paper is concerned with distributed Kalman filtering for linear time-varying systems over
multiagent sensor networks. We propose a diffusion Kalman filtering algorithm based on the …

In this paper, we introduce three novel distributed Kalman filtering (DKF) algorithms for
sensor networks. The first algorithm is a modification of a previous DKF algorithm presented …

We study the problem of distributed Kalman filtering and smoothing, where a set of nodes is
required to estimate the state of a linear dynamic system from in a collaborative manner. Our …

The problem of distributed Kalman filtering (DKF) for sensor networks is one of the most
fundamental distributed estimation problems for scalable sensor fusion. This paper …

This article is concerned with developing a novel distributed Kalman filtering algorithm over
wireless sensor networks based on randomized consensus strategy. Compared with …