Distributed fusion estimation for multisensor multirate systems with stochastic observation multiplicative noises
type: Item
instance of: scholarly article
title: Distributed fusion estimation for multisensor multirate systems with stochastic observation multiplicative noises
zbMATH Open document ID: 1407.93382
DOI: 10.1155/2014/373270
author: Peng Fangfang
author: Sun Shuli
published in: Mathematical Problems in Engineering
publication date: 2019-02-08T00:00:00Z
review text: Summary: This paper studies the fusion estimation problem of a class of multisensor multirate systems with observation multiplicative noises. The dynamic system is sampled uniformly. Sampling period of each sensor is uniform and the integer multiple of the state update period. Moreover, different sensors have the different sampling rates and observations of sensors are subject to the stochastic uncertainties of multiplicative noises. At first, local filters at the observation sampling points are obtained based on the observations of each sensor. Further, local estimators at the state update points are obtained by predictions of local filters at the observation sampling points. They have the reduced computational cost and a good real-time property. Then, the cross-covariance matrices between any two local estimators are derived at the state update points. At last, using the matrix weighted optimal fusion estimation algorithm in the linear minimum variance sense, the distributed optimal fusion estimator is obtained based on the local estimators and the cross-covariance matrices. An example shows the effectiveness of the proposed algorithms.
Mathematics Subject Classification ID: 93E11
Mathematics Subject Classification ID: 93C55
Mathematics Subject Classification ID: 62M20
zbMATH DE Number: 7016287
Wikidata QID: Q59064756
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2014/373270
OpenAlex ID: W1997407019
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description: scientific article; zbMATH DE number 7016287