Convergence of optimal linear estimator with multiplicative and time-correlated additive measurement noises

dc.contributor.authorLiu, W.
dc.contributor.authorShi, P.
dc.date.issued2019
dc.description.abstractIn 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.
dc.description.statementofresponsibilityWei Liu, Peng Shi
dc.identifier.citationIEEE Transactions on Automatic Control, 2019; 64(5):2190-2197
dc.identifier.doi10.1109/TAC.2018.2869467
dc.identifier.issn0018-9286
dc.identifier.issn1558-2523
dc.identifier.orcidShi, P. [0000-0001-6295-0405] [0000-0001-8218-586X] [0000-0002-0864-552X] [0000-0002-1358-2367] [0000-0002-5312-5435]
dc.identifier.urihttp://hdl.handle.net/2440/121014
dc.language.isoen
dc.publisherIEEE
dc.relation.granthttp://purl.org/au-research/grants/arc/DP170102644
dc.rights© 2018 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.
dc.source.urihttps://doi.org/10.1109/tac.2018.2869467
dc.subjectConvergence; multiplicative noises; optimal linear estimator; state error covariance matrix; time correlated
dc.titleConvergence of optimal linear estimator with multiplicative and time-correlated additive measurement noises
dc.typeJournal article
pubs.publication-statusPublished

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