0431324 20240103204557.920140912235959.9 7 s. C cav_un_epca*0431321978-989-758-039-0468-474Lisabon, PortugalskoInstitute for Systems and Technologies of Information, Control and Communication (INSTICC)2014 Bayesian analysis Kalman filter distributed estimation cav_un_auth*0242543 Dedecius Kamil Adaptivní systémy Department of Adaptive Systems AS AS UTIA-B Department of Adaptive Systems Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2014/AS/dedecius-0431324.pdf GP14-06678P GA ČR CZ cav_un_auth*0303543 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. cav_un_auth*0305694 11th International Conference on Informatics in Control, Automation and Robotics - ICINCO 2014 Vien 01.09.2014-03.09.2014 AT 2015 BB 1 PR RVO:67985556 http://hdl.handle.net/11104/0236077 S 2014 cav_un_epca*0431321 Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics (ICINCO) 978-989-758-039-0 468 474 Lisabon, Portugalsko Institute for Systems and Technologies of Information, Control and Communication (INSTICC) 2014