A Soft-Decision Fusion Approach for Multiple-Sensor Distributed Binary Detection Systems

A new soft-decision fusion approach is formulated for multiple-sensor distributed binary detection systems according to Neyman-Pearson criterion. The fusion rule of the proposed approach is derived. Unlike the published studies, the fusion rule of the proposed approach combines reliability terms weighted by the corresponding confidence levels to derive a final binary global decision. The proposed soft-decision approach is illustrated with simulated examples highlighting its performance and benefits of fusing the reliability terms weighted by the sensor confidence levels. The results show that the proposed approach is simple and efficient.