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Proceedings Paper

Automatic processing and modeling of GPR data for pavement thickness and properties
Author(s): Gary R. Olhoeft; Stanley S. Smith III
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Paper Abstract

A GSSI SIR-8 with 1 GHz air-launched horn antennas has been modified to acquire data from a moving vehicle. Algorithms have been developed to acquire the data, and to automatically calibrate, position, process, and full waveform model it without operator intervention. Vehicle suspension system bounce is automatically compensated (for varying antenna height). Multiple scans are modeled by full waveform inversion that is remarkably robust and relatively insensitive to noise. Statistical parameters and histograms are generated for the thickness and dielectric permittivity of concrete or asphalt pavements. The statistical uncertainty with which the thickness is determined is given with each thickness measurement, along with the dielectric permittivity of the pavement material and of the subgrade material at each location. Permittivities are then converted into equivalent density and water content. Typical statistical uncertainties in thickness are better than 0.4 cm in 20 cm thick pavement. On a Pentium laptop computer, the data may be processed and modeled to have cross-sectional images and computed pavement thickness displayed in real time at highway speeds.

Paper Details

Date Published: 27 April 2000
PDF: 6 pages
Proc. SPIE 4084, Eighth International Conference on Ground Penetrating Radar, (27 April 2000); doi: 10.1117/12.383560
Show Author Affiliations
Gary R. Olhoeft, GRORADAR (United States)
Stanley S. Smith III, Geo-Recovery Systems Inc. (United States)

Published in SPIE Proceedings Vol. 4084:
Eighth International Conference on Ground Penetrating Radar
David A. Noon; Glen F. Stickley; Dennis Longstaff, Editor(s)

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