A Study of Acoustic Fluctuations from Basin-Scale Pulse Transmissions

Abstract

The long-term goal of this research is to develop our understanding of long-range oceanic pulse propagation through random sound speed fields, like those caused by internal waves, so that we can use acoustic fluctuations like temporal, vertical, and horizontal coherence to infer average internal wave spectral parameters. The scientific objective of this work is to develop analytical expressions for temporal, vertical, and horizontal coherence of the acoustic field as a function of internal-wave model parameters. Analytical results for these second moments are important because they eliminate the need for time consuming Monte-Carlo runs and they allow an efficient treatment of the inverse problem[3]. A key element of this work is understanding the limits of geometrical optics (GO) at frequencies of order 75-Hz. It has been shown that acoustic fluctuations from energy which has ensonified the upper few hundred meters of the ocean cannot be explained using the Garrett-Munk (GM) internal wave model[3], so a secondary, oceanographic objective of this work is to explore upper ocean internal wave models.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1998
Accession Number
ADA551567

Entities

People

  • John A. Colosi

Organizations

  • Woods Hole Oceanographic Institution

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Acoustic Fields
  • Acoustic Tomography
  • Acoustic Waves
  • Born Approximations
  • Data Analysis
  • Electronic Mail
  • Energy Levels
  • Engineering
  • Fresnel Zones
  • Internal Waves
  • Observation
  • Ocean Acoustic Tomography
  • Signal Processing
  • Tomography
  • Travel Time
  • Wave Propagation
  • Waves

Fields of Study

  • Physics

Readers

  • Acoustical Oceanography.
  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.
  • Computational Modeling and Simulation

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference