An information-theoretic approach to distributed state estimation - Battistelli, G.; Chisci, L.; Morrocchi, S.; Papi, Francesco (2011)
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.