On Autocovariance Least-Squares Method for Noise Covariance Matrices Estimation

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F17%3A43931666" target="_blank" >RIV/49777513:23520/17:43931666 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/TAC.2016.2571899" target="_blank" >http://dx.doi.org/10.1109/TAC.2016.2571899</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TAC.2016.2571899" target="_blank" >10.1109/TAC.2016.2571899</a>

Result language
angličtina
Original language name
On Autocovariance Least-Squares Method for Noise Covariance Matrices Estimation
Original language description
The technical note focuses on the estimation of the noise covariance matrices of the state space models. Stress is laid on the autocovariance least-squares method providing unbiased estimates of the noise covariance matrices of linear systems. In particular, two topics are discussed; first, selection of the predictor gain as a key parameter of the method, second, generalization of the method for linear systems with a time-varying measurement equation. The theoretical results are illustrated in numerical examples.
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
—
OECD FORD branch
20205 - Automation and control systems

Project
<a href="/en/project/GC16-19999J" target="_blank" >GC16-19999J: Cooperative Approaches to Design of Nonlinear Filters</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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