Covariance Intersection fusion with element-wise partial knowledge of correlation

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F22%3A43968184" target="_blank" >RIV/49777513:23520/22:43968184 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1016/j.automatica.2022.110168" target="_blank" >https://doi.org/10.1016/j.automatica.2022.110168</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.automatica.2022.110168" target="_blank" >10.1016/j.automatica.2022.110168</a>

Result language
angličtina
Original language name
Covariance Intersection fusion with element-wise partial knowledge of correlation
Original language description
Covariance Intersection fusion is a linear rule for combining estimates. If the cross-correlation matrix of the errors of two estimates is unknown, the rule is bound-optimal. This paper elaborates the case when some elements of the cross-correlation matrix are known. Techniques for constructing a family of upper bounds of the joint mean square error matrix are introduced. All configurations for the fusion of up to four estimates are considered explicitly. The techniques are also applicable for the fusion of more than four estimates.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20205 - Automation and control systems

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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