Error tolerant dual-hydrophone localization in underwater sensor networks

Abstract

In this paper, we propose an Error Tolerant Dual-Hydrophone Localization method, i.e., ET-DHL, in underwater sensor networks (USNs). To reduce the impact of the node uncertainty, measurement uncertainty, poor link quality and long latency for underwater localization problem, ET-DHL adds bit-level probability to process the binary sequence. Different from our previous work PCM, each dual-hydrophone node in ET-DHL leverages different probabilities based on TDOA to distinguish which half-plane the source lies in, and ET-DHL takes the sum of expectations of all small regions by normalizing all weighted probability to localize the source. The proposed design is evaluated through extensive simulations, evaluation results demonstrate that ET-DHL can effectively locate the acoustic source with good robustness for node location error, node angle error and measurement uncertainty.