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A signal processing methodology for assessing the performance of ASTM standard test methods for GPR systems

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TLDR
This work proposes a GPR signal processing methodology, calibrated and validated on the basis of a consistent amount of data collected by means of laboratory-scale tests, to assess the performance of the above standard test methods for GPR systems.
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This article is published in Signal Processing.The article was published on 2017-03-01 and is currently open access. It has received 27 citations till now. The article focuses on the topics: Ground-penetrating radar.

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Citations
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Journal ArticleDOI

Signal processing of GPR data for road surveys

TL;DR: Results have proven the viability of the proposed signal processing method for data acquired on flexible pavements using GPR, provided recommendations on use of specific processing stages depending on survey requirements and quality of the raw dataset.
Journal ArticleDOI

Integration of InSAR and GPR techniques for monitoring transition areas in railway bridges

TL;DR: In this article, the integration of ground penetrating radar (GPR) and the Interferometric Synthetic Aperture Radar (InSAR) techniques for the monitoring of the rail-abutment transition area in railway bridges is reported.
Journal ArticleDOI

Railway ballast condition assessment using ground-penetrating radar – An experimental, numerical simulation and modelling development

TL;DR: In this article, a ground-penetrating radar (GPR)-based assessment of railway ballast which was progressively fouled with a fine-grained silty soil material was reported.
References
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Journal ArticleDOI

Signal-to-noise Ratio Enhancement in Multichannel GPR Data via the Karhunen-Loeve Transform

TL;DR: Zhang et al. as discussed by the authors proposed to use KLT to process ground penetrating radar (GPR) signals from shallowly buried objects to eliminate the strong GPR background mostly.
Proceedings ArticleDOI

GPR data time varying deconvolution by kurtosis maximization

TL;DR: Before deconvolution, a spectral balancing method in t-f domain is applied which efficiently reduces the non-stationarity of the GPR trace using the maximum kurtosis method.
Journal ArticleDOI

Noise Reduction in a Non-Homogenous Ground Penetrating Radar Problem by Multiobjective Neural Networks

TL;DR: This paper applies artificial neural networks trained with a multiobjective algorithm to preprocess the ground penetrating radar data obtained from a finite-difference time-domain (FDTD) model at improving the target's reflected wave signal-to-noise ratio (SNR).
Journal ArticleDOI

Checking the Signal Stability in GPR Systems and Antennas

TL;DR: In this work, several tests are carried out in order to evaluate the stability of a GPR system working with three different antennas with nominal frequencies of 500, 800, and 1000 MHz.
Proceedings Article

Precision GPR measurements: assessing and compensating for instrument drift

TL;DR: In this paper, the authors address the issue of time base drift and propose ways to identify its presence, assess its influence on estimating ground penetrating radar (GPR) parameters, and to compensate for its effect.
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Q1. What contributions have the authors mentioned in the paper "A signal processing methodology for assessing the performance of astm standard test methods for gpr systems" ?

This work proposes a GPR signal processing methodology, calibrated and validated on the basis of a consistent amount of data collected by means of laboratory-scale tests, to assess the performance of the above standard test methods for GPR systems. Finally, the study is extended to GPR systems with different antenna frequencies to analyze the specific relationship between the frequency of investigation, the optimal thresholds, and the signal stability.