Inversion of Munk Sound Speed Profile Based on Hamiltonian Monte Carlo Algorithm

Abstract The velocity profile is a crucial parameter that describes the characteristics of sound waves in the ocean, playing a significant role in underwater communication and detection. Traditional methods for acquiring velocity profiles in the complex and variable marine environment are inefficient and inaccurate. To tackle this issue, this paper proposes an inversion method based on the Hamiltonian Monte Carlo algorithm. Experimental results demonstrate that this method can effectively invert velocity profile parameters. Compared to traditional methods, it not only achieves higher precision in inversion but also shows better convergence properties.