Collaborative Kalman Filtration - Bayesian Perspective

Kamil Dedecius

Abstract

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.

References

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Paper Citation


in Harvard Style

Dedecius K. (2014). Collaborative Kalman Filtration - Bayesian Perspective . In Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-039-0, pages 468-474. DOI: 10.5220/0005018104680474


in Bibtex Style

@conference{icinco14,
author={Kamil Dedecius},
title={Collaborative Kalman Filtration - Bayesian Perspective},
booktitle={Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2014},
pages={468-474},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005018104680474},
isbn={978-989-758-039-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Collaborative Kalman Filtration - Bayesian Perspective
SN - 978-989-758-039-0
AU - Dedecius K.
PY - 2014
SP - 468
EP - 474
DO - 10.5220/0005018104680474