Optimal Physics - Based Detection and Classification of Objects in the Vicinity of an Uncertain Seafloor.

Abstract

A physics based approach to the design of the optimum detector is presented which merges statistical physical modeling of the acoustic scattering medium with a probabilistic description of environmental prior knowledge within a Bayesian decision theoretic framework. For the high frequency, shallow water, reverberation limited environment considered herein, the parameterization of the acoustic medium is essentially limited to modeling acoustic interaction with allisotropic seafloor microroughness with unknown horizontal wave number spectrum parameters. Simulation results, presented in terms of receiver operator characteristic (ROC) curves, aim to illustrate three principal points: (1) the cost of ignoring the bottom reverberation spatial coherence when it is present in the data; (2) the sensitivity of the likelihood ratio detector for a known environment to incorrect prior knowledge of the microroughness wavenumber spectrum; and (3) the robust performance realizable by the optimum detection algorithm that properly accounts for environmental uncertainty within a Bayesian framework.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1996
Accession Number
ADA308959

Entities

People

  • D. Alexandrou
  • L. W. Noltse

Organizations

  • Duke University

Tags

DTIC Thesaurus Topics

  • Acoustic Scattering
  • Bayesian Networks
  • Detection
  • Detectors
  • Diffraction
  • Environment
  • Frequency
  • Reverberation
  • Scattering
  • Seabed
  • Shallow Water
  • Simulations
  • Spectra

Readers

  • Acoustical Oceanography.
  • Computational Modeling and Simulation
  • Regression Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference