An information-theoretic approach to distributed state estimation

Battistelli, G.; Chisci, L.; Morrocchi, S.; Papi, Francesco

doi:10.3182/20110828-6-IT-1002.01998

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Authors

Battistelli, G.

Chisci, L.

Morrocchi, S.

Papi, Francesco

Date

2011

Type

Conference Paper

Metadata

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Citation

Battistelli, G. and Chisci, L. and Morrocchi, S. and Papi, F. 2011. An information-theoretic approach to distributed state estimation, in Bittanti, S. and Cenedese, A. and and Zampieri, S. (ed), Proceedings of the 18th World Congress of the International Federation of Automatic Control (IFAC), Aug 28-Sep 2 2011, pp. 12477-12482. Milano, Italy, Catholic University of the Sacred Heart.

Source Title

IFAC Proceedings Volumes (IFAC-PapersOnline)

DOI

10.3182/20110828-6-IT-1002.01998

ISBN

9783902661937

School

Department of Electrical and Computer Engineering

URI

http://hdl.handle.net/20.500.11937/4438

Collection

Curtin Research Publications

Abstract

It is shown that the covariance intersection fusion rule, widely used in the context of distributed estimation, has a nice information-theoretic interpretation in terms of consensus on the Kullback-Leibler average of Gaussian probability density functions (PDFs). Based on this observation, a novel distributed state estimator based on the consensus among local posterior PDFs is proposed and its stability properties are analyzed.