Performance analysis of distributed Neyman-Pearson detection systems

The performance of a distributed Neyman-Pearson detection system is considered with the decision rules of the sensors given and the decisions from different sensors being mutually independent conditioned on both hypotheses. To achieve the better performance at the fusion center for a general detection system of n > 3 sensor configuration, the necessary and sufficient conditions are derived by comparing the probability of detection at the fusion center with that of each of the sensors, with the constraint that the probability of false alarm at the fusion center is equal to that of the sensor. The conditions are related with the performances of the sensors and using the results we can predict the performance at the fusion center of a distributed detection system and can choose appropriate sensors to construct efficient distributed detection systems.