Localization using stochastic proximity embedding for underwater Acoustic Sensor Networks

Abstract

Underwater Acoustic Sensor Networks are getting increasing attention from the research community. Localization is an important functionality in any sensor network. Due to properties of the acoustic medium, terrestrial localization algorithms are not directly applicable to underwater networks. In this paper, the authors propose a modified version of Stochastic Proximity Embedding localization algorithm proposed before for terrestrial localization customized for underwater application. The algorithm was found to provide good performance in underwater scenario as it can make use of ranges between all nodes with unknown locations. Detailed study of the algorithm performance has been done and the results are reported.