Efficient Inversion in Underwater Acoustics with Iterative and Sequential Bayesian Methods

Abstract

LONG TERM GOALS: The long term goal of this project is to develop efficient inversion algorithms for successful geoacoustic parameter estimation and source localization, exploiting (fully or partially) the physics of the propagation medium. Algorithms are designed for geoacoustic inversion via the extraction features of the acoustic field. OBJECTIVES: Achieve accurate and computationally efficient geoacoustic inversion and source localization by designing estimation schemes that combine acoustic field modeling and statistical modeling. Develop methods for passive localization and inversion of environmental parameters that select features of propagation that are essential to model for accurate inversion. Implement sequential filtering methods that provide dynamic and efficient solutions for the first two objectives.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 30, 2011
Accession Number
ADA571694

Entities

People

  • Zoi Heleni Michalopoulou

Organizations

  • New Jersey Institute of Technology

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Acoustic Fields
  • Acoustic Signals
  • Acoustics
  • Bayesian Networks
  • Data Processing
  • Filters
  • Filtration
  • Frequency
  • Inversion
  • Monte Carlo Method
  • New Jersey
  • Particles
  • Physics
  • Probability
  • Probability Distributions
  • Sequential Monte Carlo Methods
  • Underwater Acoustics

Fields of Study

  • Physics

Readers

  • Computational Modeling and Simulation
  • Seismology
  • Sensor Fusion and Tracking Systems.

Technology Areas

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