Estimation of state and measurement noise covariance matrices by multi-step prediction

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F08%3A00502295" target="_blank" >RIV/49777513:23520/08:00502295 - 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

Estimation of state and measurement noise covariance matrices by multi-step prediction

Original language description

Estimation of noise covariance matrices for linear or nonlinear stochastic dynamic systems is treated. The novel off-line technique for estimation of the covariance matrices of the state and measurement noises is designed. The technique is based on the multi-step prediction error and on knowledge of the system initial condition 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 illustrated in numerical examples.

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

BC - Theory and management systems

OECD FORD branch

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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

2008

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

IFAC Proceedings Volumes (IFAC-PapersOnline)

ISSN

1474-6670

e-ISSN

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Volume of the periodical

17

Issue of the periodical within the volume

1

Country of publishing house

KR - KOREA, REPUBLIC OF

Number of pages

6

Pages from-to

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UT code for WoS article

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EID of the result in the Scopus database

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