In a shallow water waveguide, the propagation of underwater sound greatly depends on the underwater environment, including properties of the seafloor. Accurate modeling of acoustic pressure fields proves to be difficult when seafloor parameters are unknown and range-dependent. In this study, we estimate and track the range and depth of a moving continuous acoustic source using a vertical line array (VLA) of hydrophone receivers, together with an unknown time-varying slope of the bathymetry. Sequential Bayesian estimation, relying on a particle-based implementation, is combined with the parabolic equation method to model the complex pressure fields at the VLA. In particular, the Range-dependent Acoustical Model (RAM) is employed to precompute complex pressure fields on a grid that are then used for interpolation during the runtime of the particle-based processing. The complex pressure field values are utilized for matched field processing within the likelihood function employed for sequential Bayesian estimation, allowing us to leverage range-dependent underwater sound propagation for accurate source localization and bathymetry estimation. This method is evaluated with real acoustic data from the SWellEx-96 experiment. Ongoing work explores the localization and tracking of multiple moving sources, while also jointly tracking multiple geoacoustic parameters that further describe the behavior of sound propagation in the seafloor.
Watkins et al. (Wed,) studied this question.