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GPR Imaging for Deeply Buried Objects: A Comparative Study Based on Compositing of Scanning Frequencies and a Chirp Excitation Function

Department of Electrical Engineering, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
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Geosciences 2019, 9(3), 132; https://doi.org/10.3390/geosciences9030132
Received: 13 February 2019 / Revised: 8 March 2019 / Accepted: 12 March 2019 / Published: 18 March 2019
(This article belongs to the Special Issue Advances in Ground Penetrating Radar Research)
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Abstract

Compositing of ground penetrating radar (GPR) scans of differing frequencies have been found to produce cleaner images at depth using the Gaussian mixture model (GMM) feature of the expectation-maximization (EM) algorithm. GPR scans at various heights (“Stand Off”), as well as ground-based scans, have been studied. In this paper, we compare the GPR response from a chirp excitation function-based radar with the response from the EM GMM algorithm compositing process, using the same mix of frequencies. A chirp excitation pulse was found to be effective in delineating the defined buried object, but the resulting image is less sharp than the GMM EM method. View Full-Text
Keywords: ground penetrating radar; expectation-maximization; Gaussian mixture model; maximum likelihood parameter estimation; finite-difference time-domain method; GprMax ground penetrating radar; expectation-maximization; Gaussian mixture model; maximum likelihood parameter estimation; finite-difference time-domain method; GprMax
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Tilley, R.; Sadjadpour, H.R.; Dowla, F. GPR Imaging for Deeply Buried Objects: A Comparative Study Based on Compositing of Scanning Frequencies and a Chirp Excitation Function. Geosciences 2019, 9, 132.

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