Decision Fusion in a Wireless Sensor Network with a Large Number of Sensors

For a wireless sensor network (WSN) with a large number of sensors, a decision fusion rule using the total number of detections reported by local sensors for hypothesis testing, is proposed and studied. Based on a signal attenuation model where the received signal power decays as the distance from the target increases, the system level detection performance, namely probabilities of detection and false alarms, are derived and calculated. Without the knowledge of local sensors’ performances and at low signal to noise ratio (SNR), this fusion rule can still achieve very good system level detection performance if the number of sensors is sufficiently large. The problem of designing an optimum local sensor level threshold is investigated. For various system parameters, the optimal thresholds are found numerically. Guidelines on selecting the optimal local threshold have been presented.