Adaptive Decision Fusion for Distributed Passive Detection System

For decision fusion in a distributed passive detection system, the probabilities of detection of each receiver may be unknown or vary with time. An on-line adaptive decision fusion algorithm is presented. The algorithm is based on Neyman-Pearson criterion. The algorithm uses local decisions to estimate the unknown probabilities of the detection of each receiver to implement an optimal decision fusion. Computer simulation results demonstrate its feasibility and effectiveness.