% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Soldovieri:15992,
      author       = {Soldovieri, F. and Lopera, O. and Lambot, S.},
      title        = {{C}ombination of {A}dvanced {I}nversion {T}echniques for an
                      {A}ccurate {T}arget {L}ocalization via {GPR} for {D}emining
                      {A}pplications},
      journal      = {IEEE transactions on geoscience and remote sensing},
      volume       = {49},
      issn         = {0196-2892},
      address      = {New York, NY},
      publisher    = {IEEE},
      reportid     = {PreJuSER-15992},
      pages        = {451 - 461},
      year         = {2011},
      note         = {Record converted from VDB: 12.11.2012},
      abstract     = {We used advanced ground-penetrating radar (GPR) inversion
                      techniques for detecting landmines in laboratory conditions.
                      The radar data were acquired with a calibrated vector
                      network analyzer combined with an off-ground monostatic horn
                      antenna, thereby setting up a stepped-frequency
                      continuous-wave radar. Major antenna effects and
                      interactions with the soil and targets were filtered out
                      using frequency-dependent complex antenna transfer
                      functions. The proposed strategy first exploits inversion
                      approaches that are able to give an accurate
                      characterization of the antenna-soil interaction and a
                      reliable estimate of the soil permittivity. The outcomes of
                      this first phase are at the basis of the application of a
                      microwave tomographic approach based on the Born
                      approximation to achieve the imaging of the subsurface. The
                      algorithms were applied for imaging three landmines of
                      different sizes and buried at different depths in sand.
                      Although the radar system was off the ground, the results
                      showed that it was possible to reconstruct all mines,
                      including a shallow plastic mine as small as 5.6 cm in
                      diameter. This last mine was invisible in the raw radar
                      data, and the use of common GPR imaging techniques did not
                      lead to satisfactory results. The proposed integrated method
                      shows great promise for shallow subsurface imaging in a
                      demining context, particularly because it automatically
                      provides accurate information on the shallow soil dielectric
                      permittivity.},
      keywords     = {J (WoSType)},
      cin          = {IBG-3},
      ddc          = {550},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {Terrestrische Umwelt},
      pid          = {G:(DE-Juel1)FUEK407},
      shelfmark    = {Geochemistry $\&$ Geophysics / Engineering, Electrical $\&$
                      Electronic / Remote Sensing},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000285845100013},
      doi          = {10.1109/TGRS.2010.2051675},
      url          = {https://juser.fz-juelich.de/record/15992},
}