Abstract :
Distances between fusion operators are measured using a class of random belief functions. With similarity analysis, the structure of this family is extracted, for two and three information sources. The conjunctive operator, quick and associative but very isolated on a large discernment space, and the arithmetic mean are identified as outliers, while the hybrid method and six proportional conflict-redistributing rules (PCR) form a continuum. The hybrid method is showed as being central for the family of fusion methods. All the fusion operators tested with random belief functions are validated on the fusion of radar data classifiers, and show the interest of some new PCR methods
Keywords :
belief networks; inference mechanisms; radar theory; sensor fusion; uncertainty handling; Dempster-Shafer theory; PCR; arithmetic mean; conjunctive operator; decision-based measurement; fusion operator; hybrid method; information source; proportional conflict-redistributing rule; radar data classifier; random belief function; Arithmetic; Data mining; Feeds; Fusion power generation; Information analysis; Laboratories; Lattices; Radar applications; Testing; Voting; Clustering; Dempster-Shafer theory; PCR rules; dissimilarity; random belief functions;
