• DocumentCode
    1111969
  • Title

    Ground penetrating radar tomography: algorithms and case studies

  • Author

    Witten, Alan J. ; Molyneux, John E. ; Nyquist, Jonathan E.

  • Author_Institution
    Energy Div., Oak Ridge Nat. Lab., TN, USA
  • Volume
    32
  • Issue
    2
  • fYear
    1994
  • fDate
    3/1/1994 12:00:00 AM
  • Firstpage
    461
  • Lastpage
    467
  • Abstract
    Algorithms based on two inversion procedures suggested in a previous study are applied to the problem of imaging and target detection using ground penetrating radar data acquired at two sites. One inversion procedure, referred to as the Fourier transform method, employs the spatial Fourier transform of measured data and requires subsurface inhomogeneities to be relatively deep. The second inversion method does not require the data to be Fourier transformed; however, it does require the additional restriction that inhomogeneities be relatively small. This is referred to as the far-field method. These two inversion relationships are used to reconstruct images of both spatial variations-in refractive index and log likelihood function. It is found that both procedures perform well at a site where only a single isolated inhomogeneity exists. At a second site, where there are two adjacent inhomogeneities, the Fourier transform method proved superior
  • Keywords
    geophysical prospecting; geophysical techniques; inverse problems; radar applications; remote sensing by radar; terrestrial electricity; EM method; Fourier transform method; algorithm; buried object detection; far-field method; geoelectric; geophysical prospecting; ground penetrating radar tomography; imaging; inverse problem; inversion; log likelihood function; measurement technique; shallow crust structure geology; spatial Fourier transform; subsurface inhomogeneities; target detection; terrestrial electricity; Computer aided software engineering; Fourier transforms; Frequency; Geophysical measurements; Ground penetrating radar; Object detection; Pollution measurement; Refractive index; Signal processing algorithms; Tomography;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/36.295060
  • Filename
    295060