Bayesian Inversion of Seabed Scattering Data (Special Research Award in Ocean Acoustics)

Abstract

The long-term goals of this work are to improve ocean acoustic reverberation modeling and sonar performance predictions in shallow waters by developing inversion procedures to estimate seabed scattering and geoacoustic properties with uncertainties, as well as investigating the importance of various scattering processes. Important issues include: investigating the angular and frequency dependence of scattering (defining the scattering kernel), determining the dependence of scattering on physical properties of the seabed, and establishing the relative importance between scattering due to rough boundaries at the seafloor and sub-bottom interfaces or at volume inhomogeneities. These issues are all key to the ability to invert scattering and/or reflection data for seabed geoacoustic and scattering parameters, and ultimately to the practical inversion of active source reverberation data for rapid environmental assessment applications.

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Document Details

Document Type
Technical Report
Publication Date
Sep 30, 2012
Accession Number
ADA575112

Entities

People

  • Gavin A. Steininger
  • Jan Dettmer
  • Stan E. Dosso
  • W. Charles (Wilbur) Holland, Jr.

Organizations

  • Pennsylvania State University

Tags

Communities of Interest

  • Air Platforms
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Acoustics
  • Algorithms
  • Bayesian Networks
  • Computational Science
  • Data Analysis
  • Frequency
  • Inversion
  • Measurement
  • Monte Carlo Method
  • Physical Properties
  • Probability
  • Probability Distributions
  • Reflection
  • Scattering
  • Shallow Water
  • Spherical Waves
  • Wave Phenomena

Readers

  • Acoustical Oceanography.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference