Event source identification and strength estimation in wireless sensor networks
Jian Wang, Xiumei Wu, Xiaoming Hu, Xiaolin Xu · 2016
Wireless sensor networks have been widely applied in military, civilian, industrial, and environmental scenarios. Usually, sensors are assumed to have finite fixed sensing range or fine-grained signal measurement in the existing literature. We yet consider a more constrained sensing model in this paper: the sensors can sense event source signal of being at least a threshold strength and derive only binary detection reports (i.e. signal goes detected or undetected). Then we investigate the correctness probabilities of event source identification and signal strength estimation. Based upon binary detection reports from individual sensors, we introduce a concept of equivalent signal strength class and subsequently describe a probability calculation algorithm. Finally, event source identification probability and signal strength estimation probability are demonstrated under multiple varying sensor network parameters via executing our probability calculation algorithm.