Two fusion predictors for continuous-time linear systems with different types of observations

DOI10.1080/00207721003768159zbMath1259.93114OpenAlexW2077206307MaRDI QIDQ4909246

Kyung Min Lee, Haryong Song, Vladimir Shin

Publication date: 12 March 2013

Published in: International Journal of Systems Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207721003768159

zbMATH Keywords

parallel structurematrix weightsfusion formulaminimum mean square errorcontinuous-time linear systemmultisensordamper harmonic oscillatorKalman predictorsmultisensory environmentoptimal linear combination

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Estimation and detection in stochastic control theory (93E10) Linear systems in control theory (93C05)

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Cites Work

• A new fusion formula and its application to continuous-time linear systems with multisensor environment
• Generalized Millman's formula and its application for estimation problems
• New approach to information fusion steady-state Kalman filtering
• Multi-sensor optimal information fusion Kalman filters with applications
• Decentralized estimation algorithms for a backward pass fixed-interval smoother
• Optimal linear estimation fusion. I. Unified fusion rules
• Distributed optimal fusion steady-state Kalman filter for systems with coloured measurement noises
• The optimality for the distributed Kalman filtering fusion with feedback

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