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

Benedetto, Francesco and Tosti, Fabio ORCID: https://orcid.org/0000-0003-0291-9937 (2016) A signal processing methodology for assessing the performance of ASTM standard test methods for GPR systems. Signal Processing, 132. pp. 327-337. ISSN 0165-1684

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Abstract

Ground penetrating radar (GPR) is one of the most promising and effective non-destructive testing techniques (NDTs), particularly for the interpretation of the soil properties. Within the framework of international Agencies dealing with the standardization of NDTs, the American Society for Testing and Materials (ASTM) has published several standard test methods related to GPR, none of which is focused on a detailed analysis of the system performance, particularly in terms of precision and bias of the testing variable under consideration. 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. The (theoretical) expressions of the bias and variance of the estimation error are here investigated by a reduced Taylor's expansion up to the second order. Therefore, a closed form expression for theoretically tuning the optimal threshold according to a fixed target value of the GPR signal stability is proposed. 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.

Item Type: Article
Identifier: 10.1016/j.sigpro.2016.06.030
Additional Information: © 2016 Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Keywords: Ground Penetrating Radar; GPR calibration; Performance evaluation; Civil engineering application
Subjects: Construction and engineering > Built environment
Construction and engineering > Civil and structural engineering
Computing
Construction and engineering
Depositing User: Fabio Tosti
Date Deposited: 30 Jun 2016 11:30
Last Modified: 04 Nov 2024 12:16
URI: https://repository.uwl.ac.uk/id/eprint/2700

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