Doppler Velocity Log

Doppler Velocity Logs (DVLs) are crucial for accurate autonomous underwater vehicle (AUV) navigation by measuring the vehicle's velocity through acoustic reflections from the seabed. Current research heavily focuses on mitigating the challenges of incomplete or missing DVL measurements, employing deep learning architectures like neural networks (e.g., MissBeamNet, LiBeamsNet, BeamsNet) and hybrid approaches combining model-based and data-driven methods to improve velocity estimation accuracy even with limited data. These advancements significantly enhance AUV navigation reliability and operational capabilities in complex underwater environments, impacting various applications from seafloor mapping to underwater infrastructure inspection.