The Experimental Investigation of the Inverse Problem in Rough Surface Scattering of Acoustic Waves.

Abstract

This study represents an inverse problems approach to rough surface acoustical scattering, the objective being to infer certain statistical characteristics of a randomly rough surface directly from the coherently scattered pressure field. Eckart's physical-acoustical scattering model is applied to derive relationships for the probability density function and correlation function of surface heights which can be inferred directly from the scattered pressure field. Signal processing techniques are used to obtain estimates of the probability density function and correlation functions from experimental data. The experimental measurements are made of the steady-state complex scattered pressure field from a single frequency small beamwidth source incident upon a pressure release model rough surface. Comparisons are made between the characteristics inferred from the scattered pressure and the actual surface characteristics. The ability of the signal processing techniques to accurately predict the known characteristics is then evaluated. Keywords: Forward scattering; Inverse scattering; Rms surfacce height; Correlation length; Discrete Fournier transform; Bojarsky-Lewis method; Extended Prony method; Spectral estimation; Power spectrum.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1985
Accession Number
ADA158070

Entities

People

  • R. S. Bailey

Organizations

  • University of Texas at Austin

Tags

Communities of Interest

  • Air Platforms
  • C4I
  • Cyber
  • Energy and Power Technologies
  • Weapons Technologies

DTIC Thesaurus Topics

  • Acoustic Waves
  • Acoustics
  • Computer Programs
  • Discrete Fourier Transforms
  • Experimental Data
  • Frequency
  • Geometry
  • Information Science
  • Inverse Problems
  • Inverse Scattering
  • Measurement
  • Power Spectra
  • Probability
  • Probability Density Functions
  • Scattering
  • Signal Processing
  • Statistical Analysis

Fields of Study

  • Engineering
  • Physics

Readers

  • Approximation Theory.
  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.
  • Electromagnetic Wave Scattering and Antenna Radiation Engineering

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference