Distributed and centralized fusion estimation from multiple sensors with Markovian delays

Autor:	María J. García-Ligero, Aurora Hermoso-Carazo, Josefa Linares-Pérez
Rok vydání:	2012
Předmět:	Fusion Markov chain Computer science Applied Mathematics Markov process Covariance Signal Least squares Computational Mathematics symbols.namesake Control theory Fuse (electrical) symbols Smoothing
Zdroj:	Applied Mathematics and Computation. 219:2932-2948
ISSN:	0096-3003
Popis:	Least-squares linear estimation of signals from randomly delayed measurements acquired from multiple sensors with random delays modeled by homogeneous Markov chains is addressed. Assuming that the state-space model is unknown and using the information provided by the covariance functions of the processes involved in the observation equations, the signal estimation problem is studied by distributed and centralized methods to fuse the information provided by different sensors. Distributed and centralized filtering and fixed-point smoothing algorithms are derived using an innovation approach. The goodness of the proposed distributed and centralized filters and smoothers is compared by examining their respective error covariance matrices.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::3b19c3d1e5f393992acf0ceb67a5dd5c https://doi.org/10.1016/j.amc.2012.09.017 Zobrazit plný text záznamu Full Text from ScienceDirect