Heterogeneous fusion with a combined evidential, probability and OWA methods for target classification

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.