Localization of Nodes in Underwater Wireless Sensor Networks

Localization refers to the estimated position of each sensor node within a network. It's necessary since underwater sensor nodes depend on this information for reliable communication. The main challenge over here would be that the environment underwater is naturally quite different from land, posing uncertainty in sound speed variations and hence more noise in the channel. Here, the Kalman filter and extended Kalman filtering methods are explored to minimize the localization errors. This is validated by simulating the shallow water experiment and further the localization results are compared.

I. Introduction

Today, underwater wireless sensor networks (UWSNs) have numerous applications and usages in the field of deep sea exploration, marine and collection of oceanographic data, disaster aversion, pollution levels monitoring, assisted navigation and other surveillance applications. Unmanned underwater vehicles (UUVs) or autonomous underwater vehicles (AUVs), equipped with sensors are deployed to explore natural undersea resources and to collect scientific data. Thus, underwater acoustic networking forms the enabling technology for such missions. [1] Hence, it is important that whatever data is collected by them can be trusted and is useful. This is possible only when there is accurate localization of these devices. Fig. 1:

The localization scenario