• DocumentCode
    880697
  • Title

    Improved Sampling Methods for Shape Reconstruction of 3-D Buried Targets

  • Author

    Catapano, Ilaria ; Crocco, Lorenzo ; Isernia, Tommaso

  • Author_Institution
    Ist. per il Rilevamento Elettro- magnetico dell´´Ambiente, Consiglio Naz. delle Ric., Naples
  • Volume
    46
  • Issue
    10
  • fYear
    2008
  • Firstpage
    3265
  • Lastpage
    3273
  • Abstract
    This paper addresses the problem of reconstructing geometrical features of 3-D targets embedded into a nonaccessible region from multiview multistatic scattered field data. Sampling methods (SM) are simple and computationally effective approaches to pursue this task. However, their implementation requires a large number of multipolarization sources and probes. Moreover, their performances are often unsatisfactory for aspect-limited measurement configurations and lossy media. In order to tackle these drawbacks, usually faced in subsurface imaging, we propose a simplified and improved formulation based on the physical interpretation of SM. In particular, such a formulation relies on a small number of single polarization probes and exploits multifrequency data, for the first time in the framework of SM. The performances of the resulting approach are verified by monitoring 3-D regions of large extent.
  • Keywords
    buried object detection; electromagnetic wave polarisation; electromagnetic wave scattering; feature extraction; geophysical signal processing; geophysical techniques; sampling methods; 3D buried target shape reconstruction; geometrical feature reconstruction; multifrequency data; multiview multistatic scattered field data; polarization probes; sampling methods; subsurface imaging; Image reconstruction; Loss measurement; Monitoring; Performance evaluation; Polarization; Probes; Samarium; Sampling methods; Scattering; Shape; Electromagnetic scattering inverse problems; factorization method (FM); linear sampling method (LSM); microwave imaging; subsurface imaging;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/TGRS.2008.921745
  • Filename
    4637927