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Ground Penetrating Radar

  • X. Lucas TravassosEmail author
  • Mario Fernandez Pantoja
Reference work entry

Abstract

In recent years, the nondestructive testing (NDT) of structures and soils using ground penetrating radars (GPRs) has become a mature technology. The particular interest in this technique is explained by several advantages when compared to other NDT techniques: the portability of the equipment because of its moderate weight, relative low cost of the survey, reasonable budget of the initial investment, and high versatility in terms of application for different purposes and scenarios. However, the success of GPR surveys is not straightforward due to the complexity of the physical phenomena involved. The determination of the most appropriate hardware configuration (mostly, antennas and particular waveforms of electromagnetic pulses) is determined by a thorough analysis of the application (e.g., material properties and features of the buried object and host medium). In this way, an initial choice among the available electronic equipment is made by gathering the relevant information of the survey: the expected depth of the target embedded, the resolution required to identify targets of a definite size, the physical contrast between constitutive parameters of flaw and host medium, and the signal to noise ratio of the measurement due not only to electronics but also to inherent conditions of the survey (i.e., existing clutters, nonhomogeneities of the host medium, and roughness of the interface air-host). Therefore, a GPR survey is considered a multidisciplinary problem requiring contributions: from electrical engineering, to design and manufacture versatile and powerful equipment; from physics, to analyze and choose an optimum configuration for the desired application; and from computer science, to achieve proper predictions through the information provided by the measurements. This chapter introduces briefly this multidisciplinary approach by presenting first the electromagnetic phenomena leading to the detection with GPR, then by listing the characteristics of available equipment, and finally by enumerating some of the latest computer techniques for the discovery and classification of targets.

References

  1. Alkhalifeh K et al (2016) Efficient mom simulation of 3-d antennas in the vicinity of the ground. IEEE Trans Antennas Propag 64(12):5335–5344CrossRefGoogle Scholar
  2. Almeida ER et al (2016) Microwave tomography-enhanced gpr in forensic surveys: the case study of a tropical environment. IEEE J Sel Top Appl Earth Obs Remote Sens 9(1):115–124.  https://doi.org/10.1109/JSTARS.2015.2466556CrossRefGoogle Scholar
  3. Al-Qadi IL, Hazim OA, Su W, Riad SM (1995) Dielectric properties of Portland cement concrete at low radio frequencies. J Mater Civ Eng 7(3):192–198.  https://doi.org/10.1061/(ASCE)0899-1561(1995)7:3(192)CrossRefGoogle Scholar
  4. Balanis C (2005) Antenna theory: analysis and design, vol 1. Wiley, HobokenGoogle Scholar
  5. Blaricum MV, Mittra R (1975) A technique for extracting the poles and residues of a system directly from its transient response. IEEE Trans Antennas Propag 23(6):777–781.  https://doi.org/10.1109/TAP.1975.1141184CrossRefGoogle Scholar
  6. Bykztrk O, Yu T, Alberto Ortega J (2006) A methodology for determining complex permittivity of construction materials based on transmission-only coherent, wide- bandwidth free-space measurements. Cem Concr Compos 28:349–359CrossRefGoogle Scholar
  7. Caorsi S, Cevini G (2005) An electromagnetic approach based on neural networks for the gpr investigation of buried cylinders. IEEE Geosci Remote Sens Lett 2(1):3–7.  https://doi.org/10.1109/LGRS.2004.839648CrossRefGoogle Scholar
  8. Cook JC (1975) Radar transparencies of mine and tunnel rocks. Geophysics 40(5):865–885.  https://doi.org/10.1190/1.1440573CrossRefGoogle Scholar
  9. Daniels DJ (2004) Ground penetrating radar, 2nd ed. IEE London, UKGoogle Scholar
  10. Dash M, Liu H (2007) Dimensionality Reduction. Wiley.  https://doi.org/10.1002/9780470050118.ecse112
  11. De Coster A et al (2016) Fundamental analyses on layered media reconstruction using gpr and full-wave inversion in near-field conditions. IEEE Trans Geosci Remote Sens 54(9):5143–5158.  https://doi.org/10.1109/TGRS.2016.2556862CrossRefGoogle Scholar
  12. Donato LD, Crocco L (2015) Model-based quantitative cross-borehole gpr imaging via virtual experiments. IEEE Trans Geosci Remote Sens 53(8):4178–4185.  https://doi.org/10.1109/TGRS.2015.2392558CrossRefGoogle Scholar
  13. Du et al (2016) Research of fusion method of gpr tomography images based on wavelet transform. In: 2016 16th international conference on ground penetrating radar (GPR), Piscataway, pp 1–6.  https://doi.org/10.1109/ICGPR.2016.7572666
  14. Ebihara S et al (2012) Interference criterion for coaxial-fed circular dipole array antenna in a borehole. IEEE Trans Geosci Remote Sens 50(9):3510–3526.  https://doi.org/10.1109/TGRS.2011.2182517CrossRefGoogle Scholar
  15. Evans S (1963) Radio techniques for the measurement of ice thickness. Polar Rec 11(73):406410.  https://doi.org/10.1017/S0032247400053523CrossRefGoogle Scholar
  16. Fleuret F, Sahbi H (2003) Scale-invariance of support vector machines based on the triangular kernel. In: 3rd international workshop on statistical and computational theories of visionGoogle Scholar
  17. Gader et al (1999) Applications of hidden Markov models to detecting land mines with ground-penetrating radar.  https://doi.org/10.1117/12.356989
  18. Gader PD et al (2001) Landmine detection with ground penetrating radar using hidden Markov models. IEEE Trans Geosci Remote Sens 39(6):1231–1244.  https://doi.org/10.1109/36.927446CrossRefGoogle Scholar
  19. GeoRadar (2018) Ibis guardian. https://idsgeoradar.com/products/software/ibisguardian. Accessed: 2018-02-12
  20. Giannakis I et al (2016) A realistic fdtd numerical modeling framework of ground penetrating radar for landmine detection. IEEE J Sel Top Appl Earth Obs Remote Sens 9(1): 37–51.  https://doi.org/10.1109/JSTARS.2015.2468597CrossRefGoogle Scholar
  21. Gilad-Bachrach R, Navot A, Tishby N (2004) Margin based feature selection – theory and algorithms. In: Proceedings of the twenty-first International conference on machine learning. ACM, New York, ICML ‘04, p 43zbMATHGoogle Scholar
  22. González-Huici M (2013) Accurate ground penetrating radar numerical modeling for automatic detection and recognition of antipersonnel landminesGoogle Scholar
  23. Goodman (2018) Gpr slice. http://www.gpr-survey.com. Accessed: 2018-02-12
  24. GPRMax (2018) Gprmax. http://www.gprmax.com. Accessed: 2018-02-12
  25. GSSI (2018) Radan software. https://www.geophysical.com/software. Accessed: 2018-02-12
  26. Guan B et al (2017) Near-field full-waveform inversion of ground-penetrating radar data to monitor the water front in limestone. IEEE J Sel Top Appl Earth Obs Remote Sens 10(10):4328–4336.  https://doi.org/10.1109/JSTARS.2017.2743215CrossRefGoogle Scholar
  27. Haykin S, Van Veen B (2007) Signal and systems, 2nd edn. Wiley India Pvt. LimitedGoogle Scholar
  28. Hfinghoff JF, Overmeyer L (2013) Resistive loaded antenna for ground penetrating radar inside a bottom hole assembly. IEEE Trans Antennas Propag 61(12):6201–6205.  https://doi.org/10.1109/TAP.2013.2283604CrossRefGoogle Scholar
  29. Hulsenbeck et al (1926) German patent. No. 489434Google Scholar
  30. Ida N (2007) Engineering electromagneticsGoogle Scholar
  31. Jain A, Zongker D (1997) Feature selection: evaluation, application, and small sample performance. IEEE Trans Pattern Anal Mach Intell 19(2):153–158.  https://doi.org/10.1109/34.574797CrossRefGoogle Scholar
  32. Jol H (2008) Ground penetrating radar theory and applications. Elsevier Science, AmsterdamGoogle Scholar
  33. Ǩŕıžek P et al (2007) Improving stability of feature selection methods. Springer, Berlin/Heidelberg, pp 929–936Google Scholar
  34. Kwak N, Choi CH (2002) Input feature selection for classification problems. IEEE Trans Neural Netw 13(1):143–159.  https://doi.org/10.1109/72.977291CrossRefGoogle Scholar
  35. Leckebusch J (2011) Comparison of a stepped-frequency continuous wave and a pulsed gpr system. Archaeol Prospect 18(1):15–25.  https://doi.org/10.1002/arp.396CrossRefGoogle Scholar
  36. Lestari AA et al (2010) A modified bow-tie antenna for improved pulse radiation. IEEE Trans Antennas Propag 58(7):2184–2192.  https://doi.org/10.1109/TAP.2010.2048853CrossRefGoogle Scholar
  37. Leuschen CJ, Plumb RG (2001) A matched-filter-based reverse-time migration algorithm for ground-penetrating radar data. IEEE Trans Geosci Remote Sens 39(5):929–936CrossRefGoogle Scholar
  38. Liu H et al (2015) A hybrid dual-polarization gpr system for detection of linear objects. IEEE Antennas Wirel Propag Lett 14:317–320.  https://doi.org/10.1109/LAWP.2014.2363826CrossRefGoogle Scholar
  39. Liu X et al (2017) Ground penetrating radar data imaging via Kirchhoff migration method. In: 2017 international applied computational electromagnetics society symposium Italy (ACES), pp 1–2Google Scholar
  40. Madisetti V (1997) The digital signal processing handbook. Electrical engineering handbook. Taylor & FrancisGoogle Scholar
  41. Manandhar A et al (2015) Multiple-instance hidden Markov model for gpr-based landmine detection. IEEE Trans Geosci Remote Sens 53(4):1737–1745.  https://doi.org/10.1109/TGRS.2014.2346954CrossRefGoogle Scholar
  42. Mehta PK (1986) Concrete: structure, properties and materials. Prentice Hall, Englewood CliffsGoogle Scholar
  43. Missaoui O et al (2011) Land-mine detection with ground-penetrating radar using multistream discrete hidden Markov models. IEEE Trans Geosci Remote Sens 49(6): 2080–2099.  https://doi.org/10.1109/TGRS.2010.2090886CrossRefGoogle Scholar
  44. Neal A (2004) Ground-penetrating radar and its use in sedimentology: principles, problems and progress. Earth Sci Rev 66(3):261–330.  https://doi.org/10.1016/j.earscirev.2004.01.004MathSciNetCrossRefGoogle Scholar
  45. Nguyen MH, de la Torre F (2010) Optimal feature selection for support vector machines. Pattern Recogn 43(3):584–591.  https://doi.org/10.1016/j.patcog.2009.09.003CrossRefzbMATHGoogle Scholar
  46. Nicolaescu I (2013) Improvement of stepped-frequency continuous wave ground- penetrating radar cross-range resolution. IEEE Trans Geosci Remote Sens 51(1):85–92MathSciNetCrossRefGoogle Scholar
  47. Pieraccini M (2018) Noise performance comparison between continuous wave and stroboscopic pulse ground penetrating radar. IEEE Geosci Remote Sens Lett 15(2):222–226.  https://doi.org/10.1109/LGRS.2017.2781458CrossRefGoogle Scholar
  48. Qin H, Xie X (2016) Design and test of an improved dipole antenna for detecting enclosure structure defects by cross-hole gpr. IEEE J Sel Top Appl Earth Obs Remote Sens 9(1): 108–114.  https://doi.org/10.1109/JSTARS.2015.2466450CrossRefGoogle Scholar
  49. Queiroz FAA, Vieira DAG, Travassos XL (2013) Analyzing the relevant features of gpr scattered waves in time- and frequency-domain. Res Nondestruct Eval 24(2):105–123.  https://doi.org/10.1080/09349847.2012.752889CrossRefGoogle Scholar
  50. Raimundo et al (2014) Frequency modulated interrupted continuous wave signals in different radar imaging applications. In: 2014 XXXIth URSI general assembly and scientific symposium (URSI GASS), pp 1–4.  https://doi.org/10.1109/URSIGASS.2014.6929601
  51. Reeves B (2014) Noise modulated gpr: second generation technology. In: Proceedings of the 15th international conference on ground penetrating radar, pp 708–713.  https://doi.org/10.1109/ICGPR.2014.6970519CrossRefGoogle Scholar
  52. Rodriguez JB et al (2015) A prediction algorithm for data analysis in gpr-based surveys. Neurocomputing 168:464–474.  https://doi.org/10.1016/j.neucom.2015.05.081CrossRefGoogle Scholar
  53. Sagnard F, Rejiba F (2011) Wide band coplanar waveguide-fed bowtie slot antenna for a large range of ground penetrating radar applications. IET Microwaves, Antennas Propag 5(6):734–739CrossRefGoogle Scholar
  54. Sakamoto et al (2015) Frequency-domain Kirchhoff migration for near-field radar imaging. In: 2015 I.E. conference on antenna measurements applications (CAMA), pp 1–4Google Scholar
  55. Scholkopf B, Smola AJ (2001) Learning with kernels: support vector machines, regularization, optimization, and beyond. MIT Press, Cambridge, MAGoogle Scholar
  56. Shao J et al (2014) Tem horn antenna loaded with absorbing material for gpr applications. IEEE Antennas Wirel Propag Lett 13:523–527.  https://doi.org/10.1109/LAWP.2014.2311436CrossRefGoogle Scholar
  57. Shawe-Taylor J, Cristianini N (2004) Kernel methods for pattern analysis. Cambridge University Press, New YorkCrossRefGoogle Scholar
  58. Skolnik M (1980) Introduction to radar systems. Electrical engineering series. McGraw-Hill, New YorkGoogle Scholar
  59. Sun Y, Li J (2003) Time-frequency analysis for plastic landmine detection via forward-looking ground penetrating radar. IEE Proc Radar Sonar Navig 150:253CrossRefGoogle Scholar
  60. USRadar (2018) Radar studio. http://www.usradar.com/ground-penetrating-radar-gpr-software/radar-studio/. Accessed: 2018-02-12
  61. Vetterli M et al (2014) Foundations of signal processing. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  62. Yang CC, Bose NK (2005) Landmine detection and classification with complex-valued hybrid neural network using scattering parameters data set. IEEE Trans Neural Netw 16(3):743–753.  https://doi.org/10.1109/TNN.2005.844906CrossRefGoogle Scholar
  63. Zeng Z et al (2015) Improving target detection accuracy based on multipolarization mimo gpr. IEEE Trans Geosci Remote Sens 53(1):15–24.  https://doi.org/10.1109/TGRS.2014.2312937CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Federal University of Santa CatarinaJoinville/FlorianopolisBrazil
  2. 2.Universidad de GranadaGranadaSpain

Section editors and affiliations

  • Ida Nathan
    • 1
  • Norbert Meyendorf
    • 2
  1. 1.Department of Electrical and Computer EngineeringUniversity of AkronAkronUSA
  2. 2.Center for Nondestructive EvaluationIowa State UniversityAmesUSA

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