Off-line Estimation of System Noise Covariance Matrices by a Special Choice of the Filter Gain

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F07%3A00000272" target="_blank" >RIV/49777513:23520/07:00000272 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Off-line Estimation of System Noise Covariance Matrices by a Special Choice of the Filter Gain
Original language description
Estimation of noise covariance matrices for linear or nonlinear stochastic dynamic systems is treated. The stress is laid on the case when the initial state mean and covariance matrix are exactly known. The properties of the innovation sequence of the Kalman Filter and the local filters are discussed and the new off-line method for estimation of the covariance matrices of the state and the measurement noise is designed. The proposed method is based on special choice of the filter gain and it takes an advantage of the well-known standard relations from the area of state estimation techniques and least square method. The theoretical results are verified in numerical examples.
Czech name
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Czech description
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Project
<a href="/en/project/1M0572" target="_blank" >1M0572: Data, algorithms, decision making</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2007
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
IEEE International Symposium on Intelligent Signal Processing
ISBN
978-1-4244-0829-0
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
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Publisher name
IEEE
Place of publication
New York
Event location
Alcalá de Henares
Event date
Jul 5, 2007
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000252961000095

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