Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/121014
Citations
Scopus Web of Science® Altmetric
?
?
Type: Journal article
Title: Convergence of optimal linear estimator with multiplicative and time-correlated additive measurement noises
Author: Liu, W.
Shi, P.
Citation: IEEE Transactions on Automatic Control, 2019; 64(5):2190-2197
Publisher: IEEE
Issue Date: 2019
ISSN: 0018-9286
1558-2523
Statement of
Responsibility: 
Wei Liu, Peng Shi
Abstract: In this paper, the problem of convergence for the optimal linear estimator of discrete-time linear systems with multiplicative and time-correlated additive measurement noises is studied. By defining a new random vector that consists of the innovation, error, and part of the noise in the new measurement obtained from the measurement differencing method, we obtain convergence conditions of the optimal linear estimator by equivalently studying the convergence of the expectation of a random matrix where the random matrix is the product of the new vector and its transpose. It is also shown that the state error covariance matrix of the optimal linear estimator converges to a unique fixed point under appropriate conditions and, moreover, this fixed point can be obtained by solving a set of matrix equations.
Keywords: Convergence; multiplicative noises; optimal linear estimator; state error covariance matrix; time correlated
Rights: © 2018 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.
DOI: 10.1109/TAC.2018.2869467
Grant ID: http://purl.org/au-research/grants/arc/DP170102644
Appears in Collections:Aurora harvest 4
Electrical and Electronic Engineering publications

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.