Enhancing Underwater Communication by Dimension Conversion with Denoising Filters

Underwater acoustic communication is vital for various applications, including shallow and deep-water surveillance and geo-science. However, the underwater communication channel faces several challenges, such as low bandwidth and significant time delays, which limit its high-speed communication performance. The increasing need for accurate modeling of underwater communication channels over long ranges in complex environments presents considerable challenges. This paper introduces two significant novel contributions to the widely used Bellhop model for simulating acoustic. The first contribution is the conversion from a 3D to a 2D plot approach to represent communication performance parameters. The second contribution is the integration of the Kalman Filter (KF) and Extended Kalman Filter (EKF) to reduce measurement uncertainties and transducer noise. Importantly, the proposed model predicts the operating range based on the given transducer receiver (Rx) sensitivity at different transmission powers, considering bathymetry and in-situ sound speed profiles. The predicted range has been analyzed and validated using commercially available acoustic modems for both shallow and deep water. The accuracy of the predicted range for defined scenarios is approximately 91 to 92%.