Creating and sharing knowledge for telecommunications

Rumor-Robust Distributed Data Fusion

Rendas, M.-J. ; Leitão, J.

Rumor-Robust Distributed Data Fusion, Proc IEEE International Conf. on Multisensor Fusion and Integration for Intelligent Systems - MFI2010, Salt Lake City, United States, Vol. I, pp. 230 - 235, September, 2010.

Digital Object Identifier:

Abstract
We propose a novel Bayesian distributed data
fusion methodology robust to the problem of rumor, i.e., of
re-circulation of information accross the loops of a sensing &
processing network. This problem is particularly important in
mobile sensor networks where the communication graph is dynamically modified in an unpredictable manner. The approach
proposed is based on the notion of Schur dominance, and looks
for the less informative distribution that is more informative
than the state of knowledge of both nodes participating in
the fusion step, and that can result of factoring out common
information from the nodes. The paper details construction
of this dominating distribution for the case when the estimated
entity takes values in a finite set, and relates the fusion operator
proposed to existing rumor-robust methods, such as Covariance
Intersection and a more recent approach based on the notion
of Chernoff information. These methods are also revisited, and
some of their intrinsic limitations are clearly exhibited.