DocumentCode
3394805
Title
Understanding the large family of Dempster-Shafer theory´s fusion operators - a decision-based measure
Author
Osswald, C. ; Martin, A.
Author_Institution
ENSIETA, Brest
fYear
2006
fDate
10-13 July 2006
Firstpage
1
Lastpage
7
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Fusion, 2006 9th International Conference on
Conference_Location
Florence
Print_ISBN
1-4244-0953-5
Electronic_ISBN
0-9721844-6-5
Type
conf
DOI
10.1109/ICIF.2006.301631
Filename
4085917
Link To Document