• DocumentCode
    3323148
  • Title

    Electromagnetic infrastructure monitoring: The exploitation of GPR data and neural networks for multi-layered geometries

  • Author

    Caorsi, Salvatore ; Stasolla, Mattia

  • Author_Institution
    Dept. of Electron., Univ. of Pavia, Pavia, Italy
  • fYear
    2010
  • fDate
    25-30 July 2010
  • Firstpage
    4717
  • Lastpage
    4720
  • Abstract
    In this paper, an inversion ANN-based algorithm for the estimation of geophysical properties (i.e. thickness and permittivity) of subsurface layers in stratified geometries is presented. The basic procedure for the analysis of GPR scans of single subsurface layers placed over a uniform background recently proposed by the authors has been here extended and inserted into a general framework where each stratum is recursively processed.
  • Keywords
    geophysical techniques; ground penetrating radar; neural nets; artificial neural networks; electromagnetic infrastructure monitoring; geophysical properties; ground penetrating radar; multilayered geometries; single subsurface layers; Artificial neural networks; Atmospheric modeling; Feature extraction; Geometry; Ground penetrating radar; Monitoring; Permittivity; GPR; artificial neural networks; infrastructure monitoring;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International
  • Conference_Location
    Honolulu, HI
  • ISSN
    2153-6996
  • Print_ISBN
    978-1-4244-9565-8
  • Electronic_ISBN
    2153-6996
  • Type

    conf

  • DOI
    10.1109/IGARSS.2010.5650871
  • Filename
    5650871