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
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