A NEW METHOD OF DECISION FUSION FOR DISTRIBUTED MULTISENSOR: DOUBLE-HEAD TEST

Using classical Bayesian decision theory and hypothesistest method with reference to problem ofdistributed decision fusion,an important limitation is lack of flexibility since the method can't distinguish be-tween uncertainty and unknowing. Though Dempster-Shafer theory may satisfy requirement of flexibility,but it lacks rigorousness in the axiomatic definition of evidence through independent experiments. Thus,more effective method is demanded.Thomopoulos had presented a new Generalized Evidence Processing(GEP)theory. He attempted to unify the Bayesian theory with the Dampster-Shafer theory.In this paper,we present a new Double-Head Test(DHT)method that was derived by improving NeymanPearson test. The DHT is more applicable than GEP because DHT needn't exact knowledge of the a -prior probabilities of the tested hypotheses.