1887
Special Issue: Ground Penetrating Radar (GPR) Numerical Modelling Research and Practice
  • ISSN: 1569-4445
  • E-ISSN: 1873-0604
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Abstract

Abstract

Ground‐penetrating radar is an effective tool for detecting landmines and improvised explosive devices, but its performance is strongly influenced by subsurface properties as well as the characteristics of the target. To complement or replace labour‐intensive experiments on test sites, cost‐efficient electromagnetic wave propagation simulations using the finite‐difference time‐domain method are being increasingly used. However, to obtain realistic synthetic data, accurate modelling of signal alteration caused by dispersion, scattering from soil material, target contrast, shape, and inner setup, as well as the coupling effects of the antenna to the ground is required. In this study, we present a detailed three‐dimensional model of a shielded ground‐penetrating radar antenna applied to various scenarios containing metallic and non‐metallic targets buried in different soils. The frequency‐dependent intrinsic material properties of soil samples were measured with the coaxial transmission‐line technique, while a discrete random media was used to implement the heterogeneity of a gravel based on its grain‐size distribution. Our simulations show very good agreement with experimental validation data collected under controlled conditions. We accurately reproduce the amplitude, frequency, and phase of target signals, the subsurface background noise, antenna crosstalk and associated interference with target signals, and the effect of antenna elevation. The approach allows for a systematic investigation of the effects of soil, target, and sensor properties on detection performance, providing insight into novel and complex ground‐penetrating radar scenarios and the potential for a wide range of simulation possibilities for demining with ground‐penetrating radar. These investigations have the potential to improve the safety and effectiveness of landmine and improvised explosive device detection in the future, such as building a database for training deminers or developing automatic signal pattern recognition algorithms.

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2024-04-23
2024-05-22
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References

  1. Abeynayake, C. & Tran, M.D. (2016) Ground penetrating radar applications in buried improvised explosive device detection. In: 2016 international conference on electromagnetics in advanced applications (ICEAA), 2016. Piscataway, NJ: IEEE, pp. 564–567.
    [Google Scholar]
  2. Balanis, C. (2016) Antenna theory: Analysis and design. Hoboken, NJ: Wiley.
    [Google Scholar]
  3. Benedetto, A., Ciampoli, L.B., Brancadoro, M.G., Alani, A.M. & Tosti, F. (2017) A computer‐aided model for the simulation of railway ballast by random sequential adsorption process. Computer‐Aided Civil and Infrastructure Engineering, 33(3), 243–257. https://doi.org/10.1111/mice.12342
    [Google Scholar]
  4. Birchak, J.R., Gardner, C.G., Hipp, J.E. & Victor, J.M. (1974) High dielectric constant microwave probes for sensing soil moisture. Proceedings of the IEEE, 62(1), 93–98.
    [Google Scholar]
  5. Bourgeois, J. & Smith, G. (1998) A complete electromagnetic simulation of the separated‐aperture sensor for detecting buried land mines. IEEE Transactions on Antennas and Propagation, 46(10), 1419–1426. https://doi.org/10.1109/8.725272
    [Google Scholar]
  6. Bourgeois, J.M. & Smith, G.S. (1997) A complete electromagnetic simulation of a ground penetrating radar for mine detection: theory and experiment. In: IEEE Antennas and Propagation Society International Symposium 1997. Digest. Piscataway, NJ: IEEE, Vol. 2, pp. 986–989. https://doi.org/10.1109/aps.1997.631693
    [Google Scholar]
  7. Bruschini, C., Gros, B., Guerne, F., Pièce, P.Y. & Carmona, O. (1998) Ground penetrating radar and imaging metal detector for antipersonnel mine detection. Journal of Applied Geophysics, 40(1–3), 59–71. https://doi.org/10.1016/s0926‐9851(97)00038‐4
    [Google Scholar]
  8. Butler, D.K. (2003) Implications of magnetic backgrounds for unexploded ordnance detection. Journal of Applied Geophysics, 54(1–2), 111–125. https://doi.org/10.1016/j.jappgeo.2003.08.022
    [Google Scholar]
  9. Cao, Q. & Al‐Qadi, I.L. (2021) Development of a numerical model to predict the dielectric properties of heterogeneous asphalt concrete. Sensors, 21(8), 2643. https://doi.org/10.3390/s21082643
    [Google Scholar]
  10. Cassidy, N.J. (2006) A review of practical numerical modelling methods for the advanced interpretation of ground‐penetrating radar in near‐surface environments. Near Surface Geophysics, 5(1), 5–21. https://doi.org/10.3997/1873‐0604.2006014
    [Google Scholar]
  11. CAT‐UXO Ltd (2023) Collective awareness to unexploded ordnance. Available at: https://cat‐uxo.com/ [accessed 15 March 2023].
    [Google Scholar]
  12. Courant, R., Friedrichs, K. & Lewy, H. (1967) On the partial difference equations of mathematical physics. IBM Journal of Research and Development, 11(2), 215–234. https://doi.org/10.1147/rd.112.0215
    [Google Scholar]
  13. Daniels, D.J. (2008) A review of landmine detection using GPR. In: 2008 European radar conference, 2008, Amsterdam, the Netherlands. Piscataway, NJ: IEEE, pp. 280–283.
    [Google Scholar]
  14. Daniels, D.J. (2009) Ground penetrating radar for buried landmine and ied detection. In: Unexploded ordnance detection and mitigation. Berlin: Springer, pp. 89–111.
    [Google Scholar]
  15. Daniels, D.J. (2014) The impact of antenna design on short range radar performance. In: 2014 IEEE conference on antenna measurements & applications (CAMA), November 2014. Piscataway, NJ: IEEE, pp. 1–4. https://doi.org/10.1109/cama.2014.7003338
    [Google Scholar]
  16. Das, Y. (2006) Effects of soil electromagnetic properties on metal detectors. IEEE Transactions on Geoscience and Remote Sensing, 44(6), 1444–1453. https://doi.org/10.1109/tgrs.2006.870401
    [Google Scholar]
  17. Dohrmann, R. & Kaufhold, S. (2009) Three new, quick CEC methods for determining the amounts of exchangeable calcium cations in calcareous clays. Clays and Clay Minerals, 57, 338–352. https://doi.org/10.1346/CCMN.2009.0570306.
    [Google Scholar]
  18. Gao, X., Podd, F.J., van Verre, W., Daniels, D.J., Tan, Y.M. & Peyton, A.J. (2018) Simulation of ground penetrating radar for anti‐personnel landmine detection. In: 2018 17th International conference on ground penetrating radar (GPR), June 2018. Piscataway, NJ: IEEE, pp. 1–4. https://doi.org/10.1109/icgpr.2018.8441564
    [Google Scholar]
  19. Gedney, S.D. (1996) An anisotropic perfectly matched layer‐absorbing medium for the truncation of FDTD lattices. IEEE Transactions on Antennas and Propagation, 44(12), 1630–1639. https://doi.org/10.1109/8.546249
    [Google Scholar]
  20. Giannakis, I. & 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. https://doi.org/10.1109/TAP.2014.2308549
    [Google Scholar]
  21. Giannakis, I., Giannopoulos, A. & 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. https://doi.org/10.1109/jstars.2015.2468597
    [Google Scholar]
  22. Giannakis, I., Giannopoulos, A., Warren, C. & Davidson, N. (2015) Numerical modelling and neural networks for landmine detection using ground penetrating radar. In: 2015 8th International workshop on advanced ground penetrating radar (IWAGPR), July 2015. Piscataway, NJ: IEEE, pp. 1–4. https://doi.org/10.1109/iwagpr.2015.7292682
    [Google Scholar]
  23. Gonzalez‐Huici, M.A., Uschkerat, U. & Hoerdt, A. (2007) Numerical simulation of electromagnetic‐wave propagation for land mine detection using GPR. In: 2007 IEEE International geoscience and remote sensing symposium, 2007. Piscataway, NJ: IEEE, pp. 4957–4960.
    [Google Scholar]
  24. González‐Huici, M.A., Catapano, I. & Soldovieri, F. (2014) A comparative study of GPR reconstruction approaches for landmine detection. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(12), 4869–4878. https://doi.org/10.1109/jstars.2014.2321276
    [Google Scholar]
  25. González‐Huici, M.A. & Giovanneschi, F. (2013) A combined strategy for landmine detection and identification using synthetic GPR responses. Journal of Applied Geophysics, 99, 154–165. https://doi.org/10.1016/j.jappgeo.2013.08.006
    [Google Scholar]
  26. Hiller, T. (2023) Thohiller/gprgravel: v0.1.1. Available at: https://doi.org/10.5281/zenodo.8148692 [Accessed on November 10, 2023].
    [Google Scholar]
  27. ICBL‐CMC (2022) Landmine monitor 2022. ISBN: 978‐2‐9701476‐2‐6‐ Available at: http://www.the‐monitor.org/media/3352351/2022_Landmine_Monitor_web.pdf [Accessed on November 12, 2023].
    [Google Scholar]
  28. Igel, J., Takahashi, K. & Preetz, H. (2011) Electromagnetic soil properties and performance of GPR for landmine detection: How to measure, how to analyse and how to classify? In: 2011 6th International workshop on advanced ground penetrating radar (IWAGPR), July 2011. Piscataway, NJ: IEEE, pp. 1–6. https://doi.org/10.1109/iwagpr.2011.5963880
    [Google Scholar]
  29. Jiang, Z., Zeng, Z., Li, J., Liu, F. & Li, W. (2013) Simulation and analysis of GPR signal based on stochastic media model with an ellipsoidal autocorrelation function. Journal of Applied Geophysics, 99, 91–97. https://doi.org/10.1016/j.jappgeo.2013.08.005
    [Google Scholar]
  30. Kasban, H., Zahran, O., Elaraby, S.M.S., El‐kordy, M. & Abd El‐Samie, F.E. (2010) A comparative study of landmine detection techniques. Sensing and Imaging: An International Journal, 11, 89–112. https://doi.org/10.1007/s11220‐010‐0054‐x
    [Google Scholar]
  31. Keysight (2021) N1500A Materials measurement suite, technical overview. Available at: https://www.keysight.com/us/en/assets/7018‐04630/technical‐overviews/5992‐0263.pdf [Accessed on November 12, 2023].
    [Google Scholar]
  32. Khalifa, A.B. & Frigui, H. (2015) A multiple instance neuro‐fuzzy inference system for fusion of multiple landmine detection algorithms. In: 2015 IEEE International geoscience and remote sensing symposium (IGARSS), July 2015. Piscataway, NJ: IEEE. https://doi.org/10.1109/igarss.2015.7326780
    [Google Scholar]
  33. Kingsuwannaphong, T., Bräu, C. & Heberling, D. (2022) Fouled railway ballast modeling using rigid body simulation. In: 19th International conference on ground penetrating radar, October 2022. Houston, TX: Society of Exploration Geophysicists, pp. 63–66. https://doi.org/10.1190/gpr2022‐073.1
    [Google Scholar]
  34. Lameri, S., Lombardi, F., Bestagini, P., Lualdi, M. & Tubaro, S. (2017) Landmine detection from GPR data using convolutional neural networks. In: 2017 25th European signal processing conference (EUSIPCO), August 2017. Piscataway, NJ: IEEE, pp. . https://doi.org/10.23919/eusipco.2017.8081259
    [Google Scholar]
  35. Liu, L., Li, Z., Arcone, S., Fu, L. & Huang, Q. (2013) Radar wave scattering loss in a densely packed discrete random medium: Numerical modeling of a box‐of‐boulders experiment in the MIE regime. Journal of Applied Geophysics, 99, 68–75. https://doi.org/10.1016/j.jappgeo.2013.08.022
    [Google Scholar]
  36. Loewer, M. (2018) On the frequency‐dependence of electrical soil properties and their influence on ground‐penetrating radar. Ph.D. thesis, Technical University of Berlin, Germany.
    [Google Scholar]
  37. Loewer, M., Günther, T., Igel, J., Kruschwitz, S., Martin, T. & Wagner, N. (2017) Ultra‐broad‐band electrical spectroscopy of soils and sediments—a combined permittivity and conductivity model. Geophysical Journal International, 210(3), 1360–1373. https://doi.org/10.1093/gji/ggx242
    [Google Scholar]
  38. Loewer, M. & Igel, J. (2016) FDTD simulation of GPR with a realistic multi‐pole Debye description of lossy and dispersive media. In: 2016 16th International conference on ground penetrating radar (GPR), June 2016. Piscataway, NJ: IEEE, pp. 1–5. https://doi.org/10.1109/icgpr.2016.7572599
    [Google Scholar]
  39. Loewer, M., Igel, J. & Wagner, N. (2016) Spectral decomposition of soil electrical and dielectric losses and prediction of in situ GPR performance. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(1), 212–220. https://doi.org/10.1109/JSTARS.2015.2424152
    [Google Scholar]
  40. Lopera, O. & Milisavljevic, N. (2007) Prediction of the effects of soil and target properties on the antipersonnel landmine detection performance of ground‐penetrating radar: a Colombian case study. Journal of Applied Geophysics, 63, 13–23. https://doi.org/10.1016/j.jappgeo.2007.02.002
    [Google Scholar]
  41. Lopera, O., Milisavljević, N., Daniels, D., Gauthier, A. & Macq, B. (2008) A time frequency domain feature extraction algorithm for landmine identification from GPR data. Near Surface Geophysics, 6(6), 411–421. https://doi.org/10.3997/1873‐0604.2008029
    [Google Scholar]
  42. Missaoui, O., Frigui, H. & Gader, P. (2010) Model level fusion of edge histogram descriptors and Gabor wavelets for landmine detection with ground penetrating radar. In: 2010 IEEE international geoscience and remote sensing symposium, July 2010. Piscataway, NJ: IEEE, pp. 3378–3381. https://doi.org/10.1109/igarss.2010.5650350
    [Google Scholar]
  43. Montoya, T. & Smith, G. (1999) Land mine detection using a ground‐penetrating radar based on resistively loaded VEE dipoles. IEEE Transactions on Antennas and Propagation, 47(12), 1795–1806. https://doi.org/10.1109/8.817655
    [Google Scholar]
  44. Oguz, U. & Gurel, L. (2002) Frequency responses of ground‐penetrating radars operating over highly lossy grounds. IEEE Transactions on Geoscience and Remote Sensing, 40(6), 1385–1394. https://doi.org/10.1109/tgrs.2002.800437
    [Google Scholar]
  45. Pantoja, J.J., Gutierrez, S., Pineda, E., Martinez, D., Baer, C. & Vega, F. (2020) Modeling and measurement of complex permittivity of soils in UHF. IEEE Geoscience and Remote Sensing Letters, 17(7), 1109–1113. https://doi.org/10.1109/LGRS.2019.2942181
    [Google Scholar]
  46. Peplinski, N., Ulaby, F. & Dobson, M. (1995) Dielectric properties of soils in the 0.3–1.3‐GHz range. IEEE Transactions on Geoscience and Remote Sensing, 33(3), 803–807. https://doi.org/10.1109/36.387598
    [Google Scholar]
  47. Prado, J., Filipe, S. & Marques, L. (2015) Bayesian sensor fusion for multi‐platform landmines detection. In: 2015 European conference on mobile robots (ECMR), 9 2015. Piscataway, NJ: IEEE, pp. 1–6. https://doi.org/10.1109/ecmr.2015.7324194
    [Google Scholar]
  48. Preetz, H., Altfelder, S. & Igel, J. (2008) Tropical soils and landmine detection—an approach for a classification system. Soil Science Society of America Journal, 72(1), 151–159. https://doi.org/10.2136/sssaj2007.0065
    [Google Scholar]
  49. Schennen, S., Wagner, N., Günther, T. & Igel, J. (2021) Broadband dielectric spectroscopy with coaxial transmission line technique—a new inversion approach. In: 2021 13th International conference on electromagnetic wave interaction with water and moist substances (ISEMA), 2021. Piscataway, NJ: IEEE, pp. 1–5.
    [Google Scholar]
  50. Schwing, M., Chen, Z., Scheuermann, A. & Wagner, N. (2014) Non‐destructive coaxial transmission line measurements for dielectric soil characterization. In: 2014 IEEE Sensors Applications Symposium (SAS), February 2014. Piscataway, NJ: IEEE, pp. 248–252. https://doi.org/10.1109/sas.2014.6798955
    [Google Scholar]
  51. Stadler, S. & Igel, J. (2022) Developing realistic FDTD GPR antenna surrogates by means of particle swarm optimization. IEEE Transactions on Antennas and Propagation, 70(6), 4259–4272. https://doi.org/10.1109/TAP.2022.3142335
    [Google Scholar]
  52. Takahashi, K., Igel, J., Preetz, H. & Sato, M. (2014) Influence of heterogeneous soils and clutter on the performance of ground‐penetrating radar for landmine detection. IEEE Transactions on Geoscience and Remote Sensing, 52(6), 3464–3472. https://doi.org/10.1109/TGRS.2013.2273082
    [Google Scholar]
  53. Takahashi, K., Preetz, H. & Igel, J. (2011) Soil properties and performance of landmine detection by metal detector and ground‐penetrating radar — soil characterisation and its verification by a field test. Journal of Applied Geophysics, 73(4), 368–377. https://doi.org/10.1016/j.jappgeo.2011.02.008
    [Google Scholar]
  54. Takahashi, K. & Sato, M. (2008) A hand‐held dual‐sensor system using impulse GPR for demining. In: 2008 IEEE international conference on ubiquitous wireless broadband, September 2008. Piscataway, NJ: IEEE, pp. 157–160. https://doi.org/10.1109/icuwb.2008.4653440
    [Google Scholar]
  55. Torrione, P. & Collins, L.M. (2007) Texture features for antitank landmine detection using ground penetrating radar. IEEE Transactions on Geoscience and Remote Sensing, 45(7), 2374–2382. https://doi.org/10.1109/TGRS.2007.896548
    [Google Scholar]
  56. Travassos, X.L., Avila, S.L. & Ida, N. (2018) Artificial neural networks and machine learning techniques applied to ground penetrating radar: a review. Applied Computing and Informatics, 17(2), 296–308. https://doi.org/10.1016/j.aci.2018.10.001
    [Google Scholar]
  57. Wagner, N., Emmerich, K., Bonitz, F. & Kupfer, K. (2011) Experimental investigations on the frequency‐and temperature‐dependent dielectric material properties of soil. IEEE Transactions on Geoscience and Remote Sensing, 49(7), 2518–2530.
    [Google Scholar]
  58. Wagner, N., Müller, B., Kupfer, K., Schwing, M. & Scheuermann, A. (2010) Broadband electromagnetic characterization of two‐port rod based transmission lines for dielectric spectroscopy in soils. In: Proceedings of the first European Conference on moisture measurement, Aquametry 2010. . Weimar, Germany: MFPA Weimar, pp. 228–237.
    [Google Scholar]
  59. Warren, C. (2022) gprmax Github repository. Available at: https://github.com/gprMax/gprMax, commit=430f134, [Accessed on April 14, 2022].
    [Google Scholar]
  60. Warren, C. & 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. https://doi.org/10.1190/1.3548506
    [Google Scholar]
  61. Warren, C., Giannopoulos, A. & Giannakis, I. (2016) gprMax: open source software to simulate electromagnetic wave propagation for ground penetrating radar. Computer Physics Communications, 209, 163–170. https://doi.org/10.1016/j.cpc.2016.08.020
    [Google Scholar]
  62. Warren, C., Giannopoulos, A., Gray, A., Giannakis, I., Patterson, A., Wetter, L. et al. (2019) A CUDA‐based GPU engine for gprMax: open source FDTD electromagnetic simulation software. Computer Physics Communications, 237, 208–218. https://doi.org/10.1016/j.cpc.2018.11.007
    [Google Scholar]
  63. Wilson, J.N., Gader, P., Lee, W., Frigui, H. & Ho, K.C. (2007) A large‐scale systematic evaluation of algorithms using ground‐penetrating radar for landmine detection and discrimination. IEEE Transactions on Geoscience and Remote Sensing, 45(8), 2560–2572. https://doi.org/10.1109/TGRS.2007.900993
    [Google Scholar]
  64. Zadhoush, H., Giannopoulos, A. & Giannakis, I. (2021) Optimising the complex refractive index model for estimating the permittivity of heterogeneous concrete models. Remote Sensing, 13(4), 723. https://doi.org/10.3390/rs13040723
    [Google Scholar]
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  • Article Type: Research Article
Keyword(s): dielectric properties; ground‐penetrating radar; modelling; soil

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