Web projektu DAR

Research Centre
Data - Algorithms - Decision Making

Established in 2005 under support of MŠMT ČR (project 1M0572)

Publications

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

Typ:

Conference paper

Authors:

Duník J., Šimandl M.

Proceedings name:

Proceedings of the 17th IFAC World Congress

Serie:

Seoul, Korea

Year:

2008

Pages:

3689-3684

ISBN:

978-3-902661-00-5

ISSN:

1474-6670

Contact:

Ing. Jindřich Duník, Ph.D. (FAV Západočeská univerzita, katedra kybernetiky)

URL (www page):

http://ifac2008.org/

attachment1:

clanek_IFAC08_JD.pdf [file]

attachment2:

poster_IFAC08_JD.pdf [file]

Anotation:

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.