Title :
Heterogeneous fusion with a combined evidential, probability and OWA methods for target classification
Author :
Pong, P. ; Morelande, M. ; Challa, S.
Author_Institution :
Jacobs Australia, Univ. of Melbourne, Melbourne, VIC, Australia
Abstract :
Fusing multiple independent sensor measurements and human intelligence reports are essential to support critical decisions in a timely manner for today´s situation awareness systems. The problem of great significance is associated with fusing Human Originated Information (HOI) with the information from other sources. Ordered Weighted Average (OWA) algorithm was proposed recently as a means to assimilate uncertain human originated information. We propose a novel method to use OWA in conjunction with Bayesian and Dempster-Shafer Theory (DST) fusion algorithms to fuse information from diverse sources and demonstrate its effectiveness using an example from literature.
Keywords :
Bayes methods; pattern classification; probability; sensor fusion; uncertainty handling; Bayesian theory; Dempster-Shafer theory; OWA methods; evidential methods; heterogeneous fusion; human intelligence reports; human originated information; multiple independent sensor measurements fusing; ordered weighted average; probability methods; target classification; Argon; Bayesian methods; History; Humans; Noise; Open wireless architecture; Pragmatics; Bayesian; Dempster Shafer Theory; Fuzzy Logic; Heterogeneous Fusion; Maritime Interdiction; OWA; Tracking;
Conference_Titel :
Information Fusion (FUSION), 2010 13th Conference on
Conference_Location :
Edinburgh
Print_ISBN :
978-0-9824438-1-1
DOI :
10.1109/ICIF.2010.5711975
