Bayesian Ambient Noise Inversion for Geoacoustic Uncertainty Estimation

Abstract

This work has three main objectives: first, quantifying the ability to resolve seabed geoacoustic parameters using ambient noise measurements. Second, comparing those estimates to the ones obtained from active source inversion methods. Third, considering the effect of the resultant uncertainties for transmission loss and sonar performance prediction. A further objective related to this effort is increasing the understanding of the experimental conditions and equipment required for the collection of ambient noise data suitable for geoacoustic inversion.

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Document Details

Document Type
Technical Report
Publication Date
Sep 30, 2011
Accession Number
ADA571872

Entities

People

  • Jan Dettmer
  • Jorge E. Quijano
  • Lisa Zurk
  • Martin Siderius
  • Stan E. Dosso

Organizations

  • University of Victoria

Tags

Communities of Interest

  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Algorithms
  • Ambient Noise
  • Bayesian Networks
  • Bottom Loss
  • Computational Science
  • Experimental Data
  • Frequency
  • Inversion
  • Losses
  • Models
  • Monte Carlo Method
  • Noise
  • Probability
  • Probability Distributions
  • Random Variables
  • Sampling
  • Uncertainty

Fields of Study

  • Environmental science

Readers

  • Acoustical Oceanography.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference