A STATISTICAL APPROACH OF NODE ESTIMATION IN UNDERWATER WIRELESS SENSOR NETWORK

Abstract

Estimating the number of active nodes in underwater wireless sensor networks is a challenging issue because a lot of factors are involved in underwater environment that create difficulties in wave propagation. The major obstacles that interfere with wave propagation in underwater network are high propagation delay, high absorption and dispersion. Although, many estimation techniques exist for node estimation in wireless sensor network but they are not efficient in underwater environment. Researchers are trying to find out more efficient method for node estimation in underwater wireless sensor network. In this paper a statistical signal processing method is proposed for node estimation in underwater wireless sensor network. Here, the nodes are considered as acoustic signal sources and their number is calculated through the cross-correlation of the acoustic signals received at three sensors placed in the network. The mean of the cross-correlation function depends on the number of signal sources and in this proposed work the mean of the cross-correlation function is used as the estimation parameter. Theoretical and simulation results are provided which reflects the validity of this cross-correlation based technique. The performance of this proposed method is evaluated by comparing the error in estimation with previous approaches.