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.
An information theoretic approach to distributed state estimation / G. Battistelli; L. Chisci; S. Morrocchi; F. Papi. - ELETTRONICO. - (2011), pp. 12477-12482. (Intervento presentato al convegno 18th IFAC World Congress tenutosi a Milano, Italy) [10.3182/20110828-6-IT-1002.01998].
An information theoretic approach to distributed state estimation
BATTISTELLI, GIORGIO;CHISCI, LUIGI;MORROCCHI, STEFANO;PAPI, FRANCESCO
2011
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.
| File | Dimensione | Formato | |
|---|---|---|---|
|
IFAC2011-1998.pdf
Accesso chiuso
Tipologia:
Versione finale referata (Postprint, Accepted manuscript)
Licenza:
Tutti i diritti riservati
Dimensione
164.46 kB
Formato
Adobe PDF
|
164.46 kB | Adobe PDF | Richiedi una copia |
I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
