Collaborative Kalman Filtration: Bayesian Perspective

0431324 - ÚTIA 2015 RIV AT eng C - Konferenční příspěvek (zahraniční konf.)
Dedecius, Kamil
Collaborative Kalman Filtration: Bayesian Perspective.
Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics (ICINCO). Lisabon, Portugalsko: Institute for Systems and Technologies of Information, Control and Communication (INSTICC), 2014, s. 468-474. ISBN 978-989-758-039-0.
[11th International Conference on Informatics in Control, Automation and Robotics - ICINCO 2014. Vien (AT), 01.09.2014-03.09.2014]
Grant CEP: GA ČR(CZ) GP14-06678P
Institucionální podpora: RVO:67985556
Klíčová slova: Bayesian analysis * Kalman filter * distributed estimation
Kód oboru RIV: BB - Aplikovaná statistika, operační výzkum
http://library.utia.cas.cz/separaty/2014/AS/dedecius-0431324.pdf

The contribution studies the problem of collaborative Kalman filtering over distributed networks with or without a fusion center from the theoretically consistent Bayesian perspective. After presenting the Bayesian derivation of the basic Kalman filter, we develop a versatile method allowing exchange of observations among the network nodes and their local incorporation. A probabilistic nodes selection technique based on prior knowledge of nodes performance is proposed to reduce the communication requirements.
Trvalý link: http://hdl.handle.net/11104/0236077