A New Local Measure of Disagreement between Belief Functions – Application to Localization
In the theory of belief functions, the disagreement between sources is often measured in terms of conflict or dissimilarity. These measures are global to the sources, and provide few information about the origin of the disagreement. We propose in this paper a “finer” measure based on the decomposition of the global measure of conflict (or distance). It allows focusing the measure on some hypotheses of interest (namely the ones likely to be chosen after fusion).We apply the proposed so called “local” measures of conflict and distance to the choice of sources for vehicle localization.We show that considering sources agreement/disagreement outperforms blind fusion.
KeywordsMovement Estimation Local Measure Rotational Component Belief Function Canonical Decomposition
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