GPR Data Processing Techniques

  • Nikos EconomouEmail author
  • Antonis Vafidis
  • Francesco Benedetto
  • Amir M. Alani
Part of the Springer Transactions in Civil and Environmental Engineering book series (STICEE)


Ground penetrating radar (GPR) is a non-destructive geophysical method that uses radar pulses to image the subsurface. Notwithstanding that it is particularly promising for soil studies, GPR is characterised by notoriously difficult automated data analysis. Hence, the focus of this chapter is to provide the reader with a deep understanding of the state of the art and open issues in the field of GPR data processing techniques as well as of the interesting application of GPR in the field of civil engineering. In particular, we present an overview on noise suppression, deconvolution, migration, attribute analysis and classification techniques for GPR data.


Ground Penetrate Radar Travel Time Curve Coherent Noise Ground Penetrate Radar Data Ground Penetrate Radar Survey 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors acknowledge the COST Action TU1208 “Civil Engineering Applications of Ground Penetrating Radar”, in support of this chapter.


  1. Alani, A.M., Aboutalebi, M., Kilic, G.: Applications of ground penetrating radar (GPR) in bridge deck monitoring and assessment. J. Appl. Geophys. 97, 45–54 (2013). doi: 10.1016/j.jappgeo.2013.04.009 CrossRefGoogle Scholar
  2. Annan, P.: GPR methods for hydrogeological studies. In: Rubin, Y., Hubbard, S.S. (eds.) Hydrogeophysics, vol. 50, pp. 185–213. Springer, Berlin (2005)CrossRefGoogle Scholar
  3. Baili, J., Lahouar, S., Hergli, M., Al-Qadi, I., Besbes, K.: GPR signal denoising by discrete wavelet transform. NDT E Int. 42, 696–703 (2009)CrossRefGoogle Scholar
  4. Bancroft, J., Guirigay, T., Isaac, H.:Enhancing a seismic image after migration using deconvolution, SEG Technical Program Expanded Abstracts, pp. 1–5 (2012)Google Scholar
  5. Bano, M.: Modelling of GPR waves for lossy media obeying a complex power law of frequency for dielectric permittivity. Geophys. Prospect. 52, 11–26 (2004)CrossRefGoogle Scholar
  6. Bano, M., Loeffler, O., Girard, J.F.: Ground penetrating radar imaging and time-domain modelling of the infiltration of diesel fuel in a sandbox experiment. C.R. Geosci. 341, 846–858 (2009)CrossRefGoogle Scholar
  7. Battista, B., Addison, A., Knapp, C.: Empirical mode decomposition operator for dewowing GPR data. J. Environ. Eng. Geophys. 14(4), 163–169 (2009)CrossRefGoogle Scholar
  8. Belina, F.A., Dafflon, B., Tronicke, J., Holliger, K.: Enhancing the vertical resolution of surface georadar data. J. Appl. Geophys. 68(1), 26–35 (2008)CrossRefGoogle Scholar
  9. Benedetto, A., Benedetto, F.: Remote sensing of soil moisture content by GPR signal processing in the frequency domain. IEEE Sens. J. 11(10), 2432–2441 (2011)CrossRefGoogle Scholar
  10. Benedetto, F., Tosti, F.: GPR spectral analysis for clay content evaluation by the frequency shift method. J. Appl. Geophys. 97, 87–96 (2013)Google Scholar
  11. Benedetto, A., Benedetto, F., De Blasiis, M.R., Giunta, G.: Reliability of signal processing technique for pavement damages detection and classification using ground penetrating radar. IEEE Sens. J. 5(3), 471–480 (2005)CrossRefGoogle Scholar
  12. Berkhout, A.J.: Least-squares inverse filtering and wavelet deconvolution. Geophysics 42, 1369–1383 (1977)CrossRefGoogle Scholar
  13. Booth, A., Linford, N., Clark, R., Murray, T.: Three-dimensional, multi-offset ground-penetrating radar imaging of archaeological targets. Arch. Prosp. 15, 93–112 (2008)CrossRefGoogle Scholar
  14. Bradford, J.H.: Applying reflection tomography in the post-migration domain to multi-fold ground-penetrating radar data. Geophysics 71, K1–K8 (2006)CrossRefGoogle Scholar
  15. Bradford, J.H.: Measuring lateral and vertical heterogeneity in vadose zone water content using multi-fold GPR with reflection tomography. Vadose Zone J. 7, 184–193 (2008)CrossRefGoogle Scholar
  16. Bradford, J., Wu, Y.: Instantaneous spectral analysis: time-frequency mapping via wavelet matching with application to contaminated-site characterization by 3D GPR. Lead. Edge 26, 1018–1023 (2007)CrossRefGoogle Scholar
  17. Brooke, A., Maillol, J.: Multi-offset ground penetrating radar data for improved imaging in areas of lateral complexity—application at a native American site. J. Appl. Geophys. 62, 167–277 (2007)CrossRefGoogle Scholar
  18. Brown, J., Nichols, J., Steinbronn, L., Bradford, J.: Improved GPR interpretation through resolution of lateral velocity heterogeneity: example from an archaeological site investigation. J. Appl. Geophys. 68, 3–8 (2009)CrossRefGoogle Scholar
  19. Carpentier, S.F.A., Horstmeyer, H., Green, A.G., Doetsch, J., Coscia, I.: Semiautomated suppression of above-surface diffractions in GPR data. Geophysics 75, J43–J50 (2010)CrossRefGoogle Scholar
  20. Cassidy, N.J.: Ground penetrating radar data processing, modelling and analysis. In: Jol, H.M. (ed.) Ground Penetrating Radar: Theory and Applications, pp. 141–176. Elsevier, Sydney (2009). ISBN 978-0-444-53348-7CrossRefGoogle Scholar
  21. Chahine, K., Baltazarta, V., Wang, Y., Déroberta, X.: Blind deconvolution via sparsity maximization applied to GPR data. Eur. J. Environ. Civ. Eng. 15(4), 575–586 (2011)CrossRefGoogle Scholar
  22. Di, Q.Y., Wang, M.Y.: Migration of ground-penetrating radar data method with a finite element and dispersion. Geophysics 69(2), 472–477 (2004)CrossRefGoogle Scholar
  23. Diamanti, N., Redman, D., Field observations and numerical models of GPR response from vertical pavement cracks. J. Appl. Geophys. (2012, in press)Google Scholar
  24. Economou, N., Vafidis, A., Spanoudakis, N.S., Hamdan, H.A., Niniou-Kindeli, V.: Application of classification methods on geophysical data from the archaeological site of Aptera, Chania, Greece. In: Near Surface Geophysics. EAGE, Istanbul (2007)Google Scholar
  25. Economou, N.: Development of GPR data processing techniques using S-transform. Ph.D dissertation at the School of Mineral Resources Engineering, Environmental Geotechnology Post-Graduate Program (2010)Google Scholar
  26. Economou, N., Vafidis, A.: Spectral balancing GPR data using time variant band-width in t-f domain. Geophysics 75(3), J19–J27 (2010)CrossRefGoogle Scholar
  27. Economou, N., Vafidis, A.: Deterministic deconvolution for GPR data in t-f domain. Near Surf. Geophys. 9(5), 427–433 (2011)Google Scholar
  28. Economou, N., Vafidis, A.: GPR data time varying deconvolution by kurtosis maximization. J. Appl. Geophys. 81, 117–121 (2012)CrossRefGoogle Scholar
  29. Economou, N., Vafidis, A., Hamdan, H., Kritikakis, G., Andronikidis, N., Dimitriadis, K.: Time varying deconvolution of GPR data in civil engineering. Nondestr. Test. Eval. 27(3), 285–292 (2012)CrossRefGoogle Scholar
  30. Flandrin, P., Rilling, G., Goncalves, P.: Empirical mode decomposition as a filter bank. IEEE Sign. Proc. Lett. 11, 112–114 (2005)CrossRefGoogle Scholar
  31. Gao, D.: Application of seismic texture model regression to seismic facies characterization and interpretation. Lead. Edge 27, 394–397 (2008)CrossRefGoogle Scholar
  32. Gray, S., Etgen, J., Dellinger, J., Whitmore, D.: Seismic migration problems and solutions. Geophysics 66(5), 1622–1640 (2001)CrossRefGoogle Scholar
  33. Huang, N.E., Shen, Z., Long, S.R., Wu, M.L., Shih, H.H., Zheng, Q., Yen, N.C., Tung, C.C., Liu, H.H.: The empirical mode decomposition and Hilbert spectrum for nonlinear and nonstationary time series analysis. Roy. Soc. Lond. Ser. A Math. Phys. Eng. Sci. 454, 903–995 (1998)CrossRefzbMATHMathSciNetGoogle Scholar
  34. Ihamouten, A., Chahine, K., Baltazart, V., Villain, G., Dérobert, X.: On the variants of Jonscher’s model for the electromagnetic characterization of concrete. IEEE Trans. Instr. Meas. 60(11), 3658–3668 (2011)CrossRefGoogle Scholar
  35. Irving, J.D., Knight, R.J.: Removal of wavelet dispersion from ground-penetrating radar data. Geophysics 68, 960–970 (2003)CrossRefGoogle Scholar
  36. Jeng, Y., Lin, C.H., Li, Y.W., Chen, C.S., Yu, H.M.: Application of sub-image multiresolution analysis of ground penetrating radar data in a study of shallow structure. J. Appl. Geophys. 73, 251–260 (2011)CrossRefGoogle Scholar
  37. Jol, H.M.: Ground Penetrating Radar: Theory and Applications. Elsevier Science, Sydney (2009). ISBN 978-0-444-53348-7Google Scholar
  38. Kadioglu, S.: Photographing layer thicknesses and discontinuities in a marble quarry with 3D GPR visualization. J. Appl. Geophys. 64, 109–114 (2008)CrossRefGoogle Scholar
  39. Kadioglu, S.: Definition of buried archaeological remains with a new 3D visualization technique of ground penetrating radar data set in temple Augustus in Ankara-Turkey. Near Surf. Geophys. Spec. Issue GPR Archaeol. 8(5), 397–406 (2010)Google Scholar
  40. Kadioglu, S.: Transparent 2d/3d half bird’s-eye view of ground penetrating radar data set in archaeology and cultural heritage, chapter 5. In: Kharfi, F. (ed.) Imaging and Radioanalytical Techniques in Interdisciplinary Research-Fundamentals and Cutting Edge Applications. InTech, Croatia (2013)Google Scholar
  41. Kadioglu, S., Daniels, J.J.: 3D visualization of integrated GPR data and EM-61 data to determine buried objects and their characteristics. J. Geophys. Eng. 5, 448–456 (2008)CrossRefGoogle Scholar
  42. Kim, J.H., Cho, S.J., Yi, M.J.: Removal of ringing noise in GPR data by signal processing. J. Geosci. 11, 75–81 (2007)CrossRefGoogle Scholar
  43. Lahouar, S.: Development of data analysis algorithms for interpretation of ground penetrating radar data. Ph.D. Dissertation, Virginia Polytechnic Institute and State University, Blacksburg, VA (2003)Google Scholar
  44. Le Bastard, C., Baltazart, V., Wang, Y., Saillard, J.: Thin pavement thickness estimation using GPR with high and super resolution methods. IEEE Trans. Geosci. Rem. Sens. 45(8), 2511–2519 (2007)CrossRefGoogle Scholar
  45. LeBastard, C., Wang, Y., Baltazart, V., Dérobert, X.: Time delay and permittivity estimation by ground penetrating radar with support vector regression. IEEE Geos. Rem. Sens. Lett. 11(4), 349–353 (2013)Google Scholar
  46. Levy, S., Oldenburg, D.W.: The deconvolution of phase shifted wavelets. Geophysics 47, 1285–1294 (1987)CrossRefGoogle Scholar
  47. Li, L., Tan, A.E.-C., Jhamb, K., Rambabu, K.: Buried object characterization using ultra-wideband ground penetrating radar. IEEE Trans. Microw. Theory Tech. 60(8), 2654–2664 (2012)CrossRefGoogle Scholar
  48. Liu, G., Fomel, S., Jin, L., Chen, X.: Seismic data stacking using local correlation. Geophysics 74, V43–V48 (2009)CrossRefGoogle Scholar
  49. Lizzi, L., Viani, F., Rocca, P., Oliveri, G., Benedetti, M., Massa, A.: Three-dimensional real-time localization of subsurface objects—from theory to experimental validation. IEEE Int. Geoscience and Remote Sensing Symp., vol. 2, pp. II-121–II-124 (2009)Google Scholar
  50. Loeffler, O., Bano, M.: Ground penetrating radar measurements in a controlled Vadose Zone: influence of the water content. Vadose Zone J. 3, 1082–1092 (2004)Google Scholar
  51. Longbottom, J., Walden, A.T., White, R.E.: Principles and application of maximum kurtosis phase estimation. Geophys. Prospect. 36, 115–138 (1998)CrossRefGoogle Scholar
  52. Manica, L., Rocca, P., Salucci, M., Carlin, M., Massa, A.: Scattering data inversion through interval analysis under Rytov approximation. 7th European Conf. on Antennas Propag., Gothenburg, Sweden, 2013Google Scholar
  53. Massa, A., Boni, A., Donelli, M.: A classification approach based on SVM for electromagnetic subsurface sensing. IEEE Trans. Geosci. Remote Sens. 43(9), 2084–2093 (2005)CrossRefGoogle Scholar
  54. McClymont, A.F., Green, A.G., Streich, R., Horstmeyer, H., Tronicke, J., Nobes, D.C., Pettinga, J., Campbell, J., Langridge, R.: Visualization of active faults using geometric attributes of 3D GPR data: an example from the Alpine Fault Zone, New Zealand. Geophysics 73, 11–23 (2008)CrossRefGoogle Scholar
  55. Neto, P., Medeiros, W.: A practical approach to correct attenuation effects in GPR data. J. Appl. Geophys. 59, 140–151 (2006)CrossRefGoogle Scholar
  56. Nuzzo, L., Quarta, T.: Improvement in GPR coherent noise attenuation using t-p and wavelet transforms. Geophysics 69(3), 789–802 (2004)CrossRefGoogle Scholar
  57. Oliveri, G., Rocca, P., Massa, A.: A Bayesian compressive sampling based inversion for imaging sparse scatterers. IEEE Trans. Geosci. Remote Sens. 49(10), 3993–4006 (2011)CrossRefGoogle Scholar
  58. Pipan, M., Baradello, L., Forte, E., Prizzon, A., Finetti, I.: 2-D and 3-D processing and interpretation of multi-fold ground penetrating radar data: a case history from an archaeological site. J. Appl. Geophys. 41, 271–292 (1999)CrossRefGoogle Scholar
  59. Pipan, M., Baradello, L., Forte, E., Finetti, I.: Ground penetrating radar study of iron age tombs in southeastern Kazakhstan. Arch. Prosp. 8, 141–155 (2001)CrossRefGoogle Scholar
  60. Pipan, M., Forte, E., Dal Moro, G., Sugan, M., Finetti, I.: Multifold ground-penetrating radar and resistivity to study the stratigraphy of shallow unconsolidated sediments. Lead. Edge 22, 876–880 (2003)CrossRefGoogle Scholar
  61. Poli, L., Oliveri, G., Rocca, P., Massa, A.: Bayesian compressive sensing approaches for the reconstruction of two-dimensional sparse scatterers under TE illumination. IEEE Trans. Geosci. Remote Sens. 51(5), 2920–2936 (2013)CrossRefGoogle Scholar
  62. Saarenketo, T., Scullion, T.: Road evaluation with ground penetrating radar. J. Appl. Geophys. 43, 119–138 (2000)CrossRefGoogle Scholar
  63. Salucci, M., Sartori, D., Anselmi, N., Randazzo, A., Oliveri, G., Massa, A.: Imaging buried objects within the second-order born approximation through a multiresolution regularized inexact-newton method, Electromagnetic Theory EMTS), Proceedings of 2013 URSI International Symposium on, 116–118 (2013).Google Scholar
  64. Schimmel, M., Gallart, J.: Frequency-dependent phase coherence for noise suppression in seismic array data. J. Geophys. Res. 112, B04303 (2007)Google Scholar
  65. Schmelzbach, C., Scherbaum, F., Tronicke, J., Dietrich, P.: Bayesian frequency-domain blind deconvolution of ground-penetrating radar data. J. Appl. Geophys. 75(4), 615–630 (2011)CrossRefGoogle Scholar
  66. Sena, A., Stoffa, P., Sen, M.: Split-step Fourier migration of GPR data in lossy media. Geophysics 71, K77–K91 (2006)CrossRefGoogle Scholar
  67. Shao, W., Bouzerdoum, A., Lam Phung, S., Lijun, S., Indraratna, B., Rujikiatkamjorn, C.: Automatic classification of ground penetrating radar signals for railway ballast assessment. IEEE Trans. Geosci. Remote Sens. 49(10), 3961–3972 (2011)CrossRefGoogle Scholar
  68. Spanoudakis, N.,Vafidis, A.: GPR data interpretation using self organizing maps. In: Near Surface Geophysics. EAGE, Istanbul (2007)Google Scholar
  69. Stockwell, R.G., Mansinha, L., Lowe, R.P.: Localization of the complex spectrum: the S-transform. IEEE Trans. Sign. Proc. 44, 998–1001 (1996)CrossRefGoogle Scholar
  70. Taner, T., Luo, Y., Kelamis, P., Kellogg, S., Craigie, E.:Frequency domain smoothing for enhanced seismic resolution, SEG Expanded Abstracts (2003)Google Scholar
  71. Todoeschuck, J.P., LaFleche, P.T., Jensen, O.G., Judge, A.S., Pilon, J.A.: Deconvolution of ground probing radar data. In: Pilon, J. (ed.) Ground Penetrating Radar, Geological Survey of Canada, pp. 227– 230 (1992)Google Scholar
  72. Turner, G.: Subsurface radar propagation deconvolution. Geophysics 59, 215–223 (1994)CrossRefGoogle Scholar
  73. Vafidis, A., Manoutsoglou, M., Hamdan, H., Andronikidis, N., Koukadaki, M., Kritikakis, G., Oikonomou, N., Spanoudakis, N.: Geophysical survey at the Omalos plateau, Chania, Crete. In Proc. of the 10th Int. Congress Bulletin of the Geological Society of Greece, vol. XXXVI, pp. 1204–1213. Thessaloniki, 2004Google Scholar
  74. Vafidis, A., Andronikidis, N., Economou, N., Panagopoulos, G., Zelilidis, A., Manoutsoglou, E.: Reprocessing and interpretation of seismic reflection data at Messara Basin, Crete, Greece. J. Balkan Geophys. Soc. 15(2), 31–40 (2012)Google Scholar
  75. Van der Baan, M.: Time-varying wavelet estimation and deconvolution by kurtosis maximization. Geophysics 73, V11–V18 (2008)CrossRefGoogle Scholar
  76. Van der Baan, M.: Bandwidth enhancement: inverse Q filtering or time-varying Wiener deconvolution? Geophysics 77(4), V133–V142 (2012)CrossRefGoogle Scholar
  77. White, R.E.: Maximum kurtosis phase correction. Geophys. Int. J. 95, 371–389 (1988)CrossRefGoogle Scholar
  78. Xia, J., Franseen, E.K., Miller, R.D., Weis, T.V.: Application of deterministic deconvolution of ground-penetrating radar data in a study of carbonate strata. J. Appl. Geophys. 56, 213–229 (2004)CrossRefGoogle Scholar
  79. Zhao, W., Tian, G., Wang, B., Shi, Z., Lin, J.: Application of 3D GPR attribute technology in archaeological investigations. Appl. Geophys. 9(3), 261–269 (2012)CrossRefGoogle Scholar
  80. Zheng, Y.F., Li, Z., Zhou, L.C., Lv, D., Ying, M., Men, Y.: Increase the accuracy of GPR in tunnel detection. Adv. Mater. Res. 183–185, 1529–1533 (2011)CrossRefGoogle Scholar
  81. Zhou, H., Wan, X., Duan, R., Li, W.: Improved stolt migration algorithm for GPR imaging using segmentation velocity model. J. Comp. Inf. Syst. 7(16), 5829–5836 (2011)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Nikos Economou
    • 1
    Email author
  • Antonis Vafidis
    • 1
  • Francesco Benedetto
    • 2
  • Amir M. Alani
    • 3
  1. 1.Applied Geophysics Lab, School of Mineral Resources EngineeringTechnical University of CreteChania, CreteGreece
  2. 2.Signal Processing for Telecommunications and Economics Lab, Department of EconomicsRoma Tre UniversityRomeItaly
  3. 3.School of Computing and TechnologyUniversity of West LondonLondonUK

Personalised recommendations