Joint Synchronization and Localization for Underwater Sensor Networks Considering Stratification Effect

In underwater wireless sensor networks, time synchronization and localization are basic requirements in many applications. A joint synchronization and localization framework is expected to provide better accuracy. In this paper, we propose a unified framework to execute synchronization and localization simultaneously taking stratification effect into account. In this method, the stratification effect of underwater medium is modeled using a ray tracing approach. The maximum likelihood (ML) estimator is derived, which is shown to be highly nonlinear and nonconvex. Therefore, we employ the Gauss-Newton algorithm to solve the original nonconvex ML problem in an iterative manner. Furthermore, the Cramér-Rao lower bound for this problem is derived as a benchmark. Simulation results indicate that the proposed method outperforms the existing methods in both accuracy and energy efficiency.