1887

Abstract

Summary

Forward modelling of Ground Penetrating Radar (GPR) is often used to facilitate interpretation of complex GPR data and as a key ingredient of full waveform inversion (FWI) processes. As general 3D full-wave electromagnetic solvers are computationally very demanding routine application of advanced GPR modelling is not popular. A novel concept for creating a fast GPR forward model based on machine learning (ML) concepts is presented. This ML-based model is trained using a dataset obtained from a realistic 3D Finite-Difference Time-Domain (FDTD) gprMax model. The fast model is trained for a specific GPR application that can be easily parametrised and have a somewhat constrained variability. However, the training uses GPR A-Scans obtained from very realistic forward models that include all complex scattering effects and antenna coupling mechanisms. To demonstrate the efficiency of the approach an application, using real GPR data, of the fast forward solver within a FWI process, using a global optimiser requiring a great number of forward model calculations, is presented producing very promising results.

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/content/papers/10.3997/2214-4609.201802546
2018-09-09
2024-04-18
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References

  1. Bengio, Y., Courville, A. and Vincent, P.
    [2013] Representation learning: A review and new perspectives. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(8), 1798–1828.
    [Google Scholar]
  2. Bourdi, T., Rhazi, J.E., Boone, F. and Ballivy, G.
    [2012] Modelling dielectric-constant values of concrete: an aid to shielding effectiveness prediction and ground-penetrating radar wave technique interpretation. Journal of Physics D: Applied Physics, 45, 1–12.
    [Google Scholar]
  3. Daniels, D.J.
    [2004] Ground Penetrating Radar. Institute of Engineering and Technology, 2nd edn.
    [Google Scholar]
  4. Giannakis, I., Giannopoulos, A. and Warren, C.
    [2018] A machine learning approach for simulating ground penetrating radar. In: 24th European Meeting of Environmental and Engineering Geophysics.
    [Google Scholar]
  5. [under review] Realistic FDTD GPR antenna models optimised using a novel linear/non-linear full waveform inversion. IEEE Transaction on Geoscience and Remote Sensing.
    [Google Scholar]
  6. Kaczmarek, P. and Pietrasinski, J.
    [2014] Principal component analysis in interpretation of A-Scan measurements in GPR system. In: 24th European Meeting of Environmental and Engineering Geophysics. 1–5.
    [Google Scholar]
  7. Kirkpatrick, S., Gelatt, C.D. and Vecchi, M.P.
    [1983] Optimization by simulated annealing. Science, 220, 671–680.
    [Google Scholar]
  8. Peplinski, N.R., Ulaby, F.T. and Dobson, M.C.
    [1995] Corrections to dielectric properties of soils in the 0.3âĂŞ1.3-GHz range. IEEE Transactions on Geoscience and Remote Sensing, 33(6), 1340.
    [Google Scholar]
  9. Shaari, A., Millard, S.G. and Bungey, J.H.
    [2004] Modelling the propagation of a radar signal through concrete as a low-pass filter. NDT&E International, 37, 237–242.
    [Google Scholar]
  10. Soutsos, M.N., Bungey, J.H., Millard, S.G., Shaw, M.R. and Patterson, A.
    [2001] Dielectric properties of concrete and their influence on radar testing. NDT&E International, 37, 237–242.
    [Google Scholar]
  11. Taflove, A. and Hagness, S.C.
    [2000] Computational Electrodynamics, the Finite-Difference Time-Domain Method. Artech House, 2nd edn.
    [Google Scholar]
  12. Tebchrany, E., Sagnard, F., Baltazart, V., Tarel, J.P. and Derobert, X.
    [2014] Assessment of statistical-based clutter reduction techniques on ground-coupled GPR data for the detection of buried objects in soils. In: 24th European Meeting of Environmental and Engineering Geophysics. 604–609.
    [Google Scholar]
  13. 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]
  14. 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]
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