Finite-horizon robust Kalman filtering for uncertain discrete time-varying systems with uncertain-covariance white noises

A finite-horizon robust Kalman filtering approach for discrete time-varying uncertain systems with additive uncertain-covariance white noises is presented. The system under consideration is subject to uncertainties in both the state and output matrices. The state and gain matrices of the filter are...

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Bibliographic Details
Published inIEEE signal processing letters Vol. 13; no. 8; pp. 493 - 496
Main Authors Zhe Dong, Zhe Dong, Zheng You, Zheng You
Format Journal Article
LanguageEnglish
Published New York IEEE 01.08.2006
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Additive white noise
Covariance matrix
Discrete-time system
Filtering
Gain
Kalman filtering
Kalman filters
Mathematical analysis
Matrices
Matrix methods
Noise robustness
robust filtering
State estimation
Time varying systems
Uncertain systems
Uncertainty
Upper bound
White noise
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Summary:A finite-horizon robust Kalman filtering approach for discrete time-varying uncertain systems with additive uncertain-covariance white noises is presented. The system under consideration is subject to uncertainties in both the state and output matrices. The state and gain matrices of the filter are optimized to give a minimal upper bound on the state estimation error covariance for all admissible uncertainties
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
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ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2006.873148