A fuzzy modeling approach to decision fusion under uncertainty

A multi-sensor decision fusion scheme is presented in which the probabiliti es associated with the local sensor decisions are known to vary in a nonran dom fashion around their design values. The uncertainties associated with t he local decisions are modeled by means of fuzzy sets. A Bayesian approach is used to design the optimum fusion rule for the case where the local sens or decisions are statistically independent across the sensors. In order to reach a crisp decision, the global Bayesian risk is defuzzified using a cri terion for mapping fuzzy sets on to the real line. The performance of the o ptimum fusion rule obtained is illustrated by means of a numerical example. (C) 2000 Elsevier Science B.V. All rights reserved.