Efficient Synchronization and Localization for Underwater Acoustic Networks

In recent years, underwater sensor networks (UWSNs) have gained significant attention from both academia and industry due to the potential benefits and unique challenges posed by the water environment. UWSNs have allowed a wide range of applications to become both feasible and effective, including coastal surveillance, environmental monitoring, undersea exploration, disaster prevention and mine reconnaissance. However, due to the high attenuation of radio waves in water, acoustic communication is considered as the most suitable communication method. Characteristics unique to underwater acoustic communications and networking, however, introduce grand challenge into almost every layer of the network protocol stack. In this dissertation work, we investigate time synchronization and localization, which are fundamental services in distributed underwater acoustic networks. The dissertation covers three major pieces of work. Firstly, we propose Mobi-Sync, a novel time synchronization scheme for mobile underwater sensor networks. It utilizes spatial correlation of node mobility and applies geometry knowledge to improve propagation delay estimation. Inspired during the research course of Mobi-Sync, we propose a practical pairwise, cross-layer, time synchronization scheme for mobile underwater sensor networks, called DA-Sync. The scheme effectively utilizes Doppler effects to improve the propagation delay estimation, and employs Kalman filter to reduce the effect of mobility. Secondly, we propose a joint solution for localization and time synchronization, in which the stratification effect of the underwater medium is considered, such that the bias in the range estimates caused by assuming sound waves travel in straight lines in water environments can be effectively compensated. By combining time synchronization and localization, the accuracy of both services are improved significantly. Thirdly, we extend the localization problem into autonomous underwater vehicles (AUVs) swarm scenario. We develop the ``Suave\u27\u27 algorithm to minimize the total localization uncertainty and reduce the negative effect from long propagation and transmission delay combined with mobility