Joint trans-dimensional inversion for water-column sound speed and seabed geoacoustic models

Abstract

This letter considers joint estimation of the water-column sound-speed profile (SSP) and seabed geoacoustic model through Bayesian inversion of ocean-acoustic data. The inversion is formulated in terms of separate trans-dimensional models for the water column (as an unknown number of nodes of a piecewise-continuous SSP) and seabed (as an unknown number of uniform layers) to intrinsically parameterize each according to the information content of the data. The inversion estimates marginal posterior probability profiles, quantifying the resolution of water-column and seabed structure. To validate the proposed method, modal-dispersion data from the New England Mud Patch, collected using hand-deployable systems, are considered.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jun 01, 2023
Source ID
10.1121/10.0019706

Entities

People

  • Julien Bonnel
  • Stan E. Dosso

Organizations

  • Office of Naval Research
  • University of Victoria

Tags

Readers

  • Acoustical Oceanography.
  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference