NDLI: Distributed descriptor Wiener state fuser

Content Provider	IEEE Xplore Digital Library
Author	Chenjian Ran Lixin Yang Zili Deng
Copyright Year	2008
Description	Author affiliation: Dept. of Autom., Heilongjiang Univ., Harbin (Chenjian Ran; Lixin Yang; Zili Deng)
Abstract	By the modem time series analysis method, based on the autoregressive moving average (ARMA) innovation model and white noise estimation theory, using the optimal fusion rule weighted by scalars for components, a distributed descriptor Wiener state fuser is presented for the linear discrete stochastic descriptor systems with multisensor. It realizes a decoupled fusion estimation for state components. In order to compute the optimal weights, the formulas of computing the cross-covariances among local state estimation errors are presented based on the cross-covariances among the white noises and local innovation processes. It can handle the fused filtering, smoothing, and prediction problems in a unified framework. Its accuracy is higher than that of each local estimator. A Monte Carlo simulation example shows its effectiveness.
Starting Page	3465
Ending Page	3469
File Size	154665
Page Count	5
File Format	PDF
ISBN	9781424421138
DOI	10.1109/WCICA.2008.4593475
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Technological innovation White noise Polynomials Filtering State estimation Stochastic processes Matrices modern time series analysis method multisensor information fusion decoupled fusion descriptor system Wiener state fuser
Content Type	Text
Resource Type	Article

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