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.

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