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Volume 20, Issue 2
  • ISSN: 1569-4445
  • E-ISSN: 1873-0604
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Abstract

ABSTRACT

Time‐zero adjustment or the true ground surface for ground penetrating radar (GPR) applications is a very important aspect and an essential factor in order to position subsurface targets, especially those located at shallow depths, at their true position in depth. As the transmitted and received signals from GPR antennas are affected by the presence of different materials with varying electromagnetic properties, adjusting the time zero appropriately is important, but often not straightforward to position accurately. This paper uses a realistic three‐dimensional numerical model of a GPR transducer in order to examine where is the best location for time zero on a GPR trace. It is shown that, in order to establish a robust and consistent time‐zero position, careful consideration is also needed around how the two‐way travel time of the reflected GPR wavelet is estimated. Starting with a simple homogeneous model with a set of different targets, a better process of time‐zero adjustment and time picking of the GPR wavelets is put forward, that is verified using further more complex and realistic heterogeneous models. Further verification is obtained by using experimental data.

© 2022 European Association of Geoscientists & Engineers © 2021 The Authors. Near Surface Geophysics published by John Wiley & Sons Ltd on behalf of European Association of Geoscientists and Engineers.
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2022-03-12
2024-04-27

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References

  1. Ahrens, J., Geveci, B. and Law, C. (2005) Paraview: An end‐user tool for large data visualization. The Visualization Handbook, Elsevier, ISBN‐13: 978‐0123875822 717.
     [Google Scholar]
  2. Al‐Qadi, I.L., Xie, W., Roberts, R. and Leng, Z. (2010) Data analysis techniques for GPR used for assessing railroad ballast in high radio‐frequency environment. Journal of Transportation Engineering, 136(4), 392–399.
     [Google Scholar]
  3. Angelis, D., Warren, C. and Diamanti, N. (2019) Preliminary development of a workflow for processing multi‐concurrent receiver GPR data. In 10th International Workshop on Advanced Ground Penetrating Radar, volume 2019. European Association of Geoscientists and Engineers, pp. 1–7.
  4. Annan, A.P. (2005) Ground‐penetrating radar. In Near‐Surface Geophysics. Society of Exploration Geophysicists, pp. 357–438.
     [Google Scholar]
  5. Annan, A.P. (2015) Depth axes and NMO correction for finite offset GPR data. Sensors & Software Inc, Technical Note, PEMD0568, 16.
  6. Benedetto, A., Tosti, F., Ciampoli, L.B. and D'Amico, F. (2017) An overview of ground‐penetrating radar signal processing techniques for road inspections. Signal Processing, 132, 201–209.
     [Google Scholar]
  7. Cassidy, N.J. (2009) Ground penetrating radar data processing, modelling and analysis. In Jol, H.M. (Ed.) Ground Penetrating Radar: Theory and Applications . Elsevier Science, pp. 141–176.
     [Google Scholar]
  8. Chen, H.W. and Huang, T.M. (1998) Finite‐difference time‐domain simulation of GPR data. Journal of Applied Geophysics, 40(1‐3), 139–163.
     [Google Scholar]
  9. Daniels, D.J. (2004) Ground Penetrating Radar, 2nd edition. Institution of Engineering and Technology.
     [Google Scholar]
  10. De Pue, J., Van Meirvenne, M. and Cornelis, W.M. (2016) Accounting for surface refraction in velocity semblance analysis with air‐coupled GPR. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(1), 60–73.
     [Google Scholar]
  11. Diamanti, N., Elliott, E.J., Jackson, S.R. and Annan, A.P. (2018) The WARR machine: system design, implementation and data. Journal of Environmental and Engineering Geophysics, 23(4), 469–487.
     [Google Scholar]
  12. Dinh, K., Gucunski, N. and Duong, T.H. (2018a) An algorithm for automatic localization and detection of rebars from GPR data of concrete bridge decks. Automation in Construction, 89, 292–298.
     [Google Scholar]
  13. Dinh, K., Gucunski, N. and Duong, T.H. (2018b) Migration‐based automated rebar picking for condition assessment of concrete bridge decks with ground penetrating radar. NDT and E International, 98, 45–54.
     [Google Scholar]
  14. Dinh, K., Gucunski, N. and Zayed, T. (2019) Automated visualization of concrete bridge deck condition from GPR data. NDT and E International, 102, 120–128.
     [Google Scholar]
  15. Ernenwein, E.G. (2006) Imaging in the ground‐penetrating radar near‐field zone: a case study from New Mexico, USA. Archaeological Prospection, 13(2), 154–156.
     [Google Scholar]
  16. Giannakis, I. and Giannopoulos, A. (2014) A novel piecewise linear recursive convolution approach for dispersive media using the finite‐difference time‐domain method. IEEE Transactions on Antennas and Propagation, 62(5), 2669–2678.
     [Google Scholar]
  17. Giannakis, I., Giannopoulos, A. and Warren, C. (2016) A realistic FDTD numerical modeling framework of ground penetrating radar for landmine detection. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(1), 37–51.
     [Google Scholar]
  18. Giannakis, I., Giannopoulos, A. and Warren, C. (2019) Realistic FDTD GPR antenna models optimized using a novel linear/nonlinear full‐waveform inversion. IEEE Transactions on Geoscience and Remote Sensing, 57(3), 1768–1778.
     [Google Scholar]
  19. Giannopoulos, A. (2005) Modelling ground penetrating radar by gprMax. Construction and Building Materials, 19(10), 755–762.
     [Google Scholar]
  20. Hussnain, M.M. and Mughal, M.J. (2011) Uniform plane wave reflection from PEC plane embedded in a nonlinear medium. Progress in Electromagnetics Research, 18, 31–42.
     [Google Scholar]
  21. Jol, H.M. (2008) Ground Penetrating Radar Theory and Applications. Elsevier.
     [Google Scholar]
  22. Kaufmann, M.S., Klotzsche, A., Vereecken, H. and van der Kruk, J. (2018) Simultaneous multi‐channel GPR measurements for soil characterization. In 17th International Conference on Ground Penetrating Radar (GPR). IEEE, pp. 287–290.
  23. Klysz, G. and Balayssac, J.P. (2007) Determination of volumetric water content of concrete using ground‐penetrating radar. Cement and Concrete Research, 37(8), 1164–1171.
     [Google Scholar]
  24. Lachowicz, J. and Rucka, M. (2017) A concept of heterogeneous numerical model of concrete for GPR simulations. In 2017 9th International Workshop on Advanced Ground Penetrating Radar (IWAGPR) . IEEE, pp. 1–4.
  25. Lauro, S.E., Mattei, E., Barone, P.M., Pettinelli, E., Vannaroni, G., Valerio, G., Comite, D. and Galli, A. (2013) Estimation of subsurface dielectric target depth for GPR planetary exploration: laboratory measurements and modeling. Journal of Applied Geophysics, 93, 93–100.
     [Google Scholar]
  26. Mai, T.C., Razafindratsima, S., Sbartaï, Z.M., Demontoux, F. and Bos, F. (2015) Non‐destructive evaluation of moisture content of wood material at GPR frequency. Construction and Building Materials, 77, 213–217.
     [Google Scholar]
  27. Mezgeen, R., Vega, P.G. and Sonia, S.A. (2018) Analysis and calibration of ground penetrating radar shielded antennas. In: 17th International Conference on Ground Penetrating Radar(GPR). IEEE, pp. 605–609.
  28. Oberröhrmann, M., Klotzsche, A., Vereecken, H. and van der Krak, J. (2013) Optimization of acquisition setup for cross‐hole: GPR full‐waveform inversion using checkerboard analysis. Near Surface Geophysics, 11(2), 197–209.
     [Google Scholar]
  29. Olhoeft, G.R. (2000) Maximizing the information return from ground penetrating radar. Journal of Applied Geophysics, 43(2‐4), 175–187.
     [Google Scholar]
  30. Peplinski, N., Ulaby, F. and Dobson, M. (1995a) Dielectric properties of soils in the 0.3‐1.3‐GHZ range. IEEE Transactions on Geoscience and Remote Sensing, 33(3), 803–807.
     [Google Scholar]
  31. Peplinski, N.R., Ulaby, F.T. and Dobson, M.C. (1995b) Corrections to “dielectric properties of soils in the 0.3‐1.3‐GHZ range”. IEEE Transactions on Geoscience and Remote Sensing, 33(6), 1340.
     [Google Scholar]
  32. Philipp, K., Jens, T., Niklas, A., Andreas, K. and Michael, W. (2018) Estimating moisture changes in concrete using GPR velocity analysis: potential and limitations. In: 17th International Conference on Ground Penetrating Radar(GPR). IEEE, pp. 664–669.
  33. Shangguan, P. and Al‐Qadi, I.L. (2014) Calibration of FDTD simulation of GPR signal for asphalt pavement compaction monitoring. IEEE Transactions on Geoscience and Remote Sensing, 53(3), 1538–1548.
     [Google Scholar]
  34. Taflove, A. and Hagness, S.C. (2005) Computational Electromagnetics: The Finite‐Difference Time‐Domain Method. Artech House.
     [Google Scholar]
  35. Viriyametanont, K., Laurens, S., Klysz, G., Balayssac, J.P. and Arliguie, G. (2008) Radar survey of concrete elements: Effect of concrete properties on propagation velocity and time zero. NDT and E International, 41(3), 198–207.
     [Google Scholar]
  36. Warren, C. and Giannopoulos, A. (2011) Creating finite‐difference time‐domain models of commercial ground‐penetrating radar antennas using Taguchi's optimization method. Geophysics, 76(2), G37–G47.
     [Google Scholar]
  37. Warren, C., Giannopoulos, A. and Giannakis, I. (2016) gprMax: open source software to simulate electromagnetic wave propagation for ground penetrating radar. Computer Physics Communications, 209, 163–170.
     [Google Scholar]
  38. Warren, C., Giannopoulos, A., Gray, A., Giannakis, I., Patterson, A., Wetter, L. and Hamrah, A. (2019) A CUDA‐based GPU engine for gprmax: open source FDTD electromagnetic simulation software. Computer Physics Communications, 237, 208–218.
     [Google Scholar]
  39. Yee, K. (1966) Numerical solution of initial boundary value problems involving Maxwell's equations in isotropic media. IEEE Transactions on Antennas and Propagation, 14(3), 302–307.
     [Google Scholar]
  40. Yelf, R. (2004) Where is true time zero? In: Proceedings of the Tenth International Conference on Ground Penetrating Radar, 2004 (GPR 2004). . IEEE, volume 1, pp. 279–282.
  41. Zadhoush, H. (2020) Numerical modelling of ground penetrating radar for optimisation of the time‐zero adjustment and complex refractive index model. PhD thesis. School of Engineering, The University of Edinburgh.
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Optimizing GPR time‐zero adjustment and two‐way travel time wavelet measurements using a realistic three‐dimensional numerical model
Near Surface Geophysics 20, 208 (2022); https://doi.org/10.1002/nsg.12193
/content/journals/10.1002/nsg.12193
/content/journals/10.1002/nsg.12193
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  • Article Type: Research Article
Keyword(s): data processing; finite‐difference; ground‐penetrating radar; modelling

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