Bayesian Theory Used in Designing the Ocean Floor Electromagnetic Sounding Experiment

Abstract

In the Bayesian formulation of inversion the information content for each unknown parameter is quantified in terms of its marginal posterior probability distribution, which defines the accuracy expected in inversion. The problem of seafloor electromagnetic sounding is defined in terms of recovering the electrical conductivity profile beneath the seafloor from measurements of the electromagnetic field. Electromagnetic inversion represents a strongly non-linear problem for which a direct solution is not available. A matched-field approach to this problem can be formulated based on Bayesian inversion theory, which provides environmental parameter estimates and their uncertainties. This paper investigates the contribution of various experimental factors to the information content of the inversion parameters aiming to recover the conductivity profile from measurements of the electromagnetic field.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2005
Accession Number
ADA439944

Entities

People

  • Marius Birsan

Organizations

  • Defence Research and Development Canada

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Computational Science
  • Conductivity
  • Data Science
  • Distribution Functions
  • Electrical Conductivity
  • Electromagnetic Fields
  • Geometry
  • Measurement
  • Probability
  • Probability Density Functions
  • Probability Distributions
  • Random Variables
  • Sampling
  • Seabed
  • Uncertainty

Readers

  • Acoustical Oceanography.
  • Electromagnetic Wave Scattering and Antenna Radiation Engineering
  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms