3D microwave imaging via preliminary support reconstruction: testing on the Fresnel 2008 database (Articolo in rivista)

Type
Label
  • 3D microwave imaging via preliminary support reconstruction: testing on the Fresnel 2008 database (Articolo in rivista) (literal)
Anno
  • 2009-01-01T00:00:00+01:00 (literal)
Alternative label
  • Catapano I, Crocco L , D'Urso M, Isernia T (2009)
    3D microwave imaging via preliminary support reconstruction: testing on the Fresnel 2008 database
    in Inverse problems (Print)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Catapano I, Crocco L , D'Urso M, Isernia T (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 25 (literal)
Rivista
Note
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • CNR, IREA, Inst Electromagnet Sensing Environm, Italian Natl Council Res, I-80124 Naples, Italy Selex Sist Integrati, I-80014 Naples, Italy Mediterranea Univ Reggio Calabria, DIMET, I-89060 Reggio Di Calabria, Italy (literal)
Titolo
  • 3D microwave imaging via preliminary support reconstruction: testing on the Fresnel 2008 database (literal)
Abstract
  • In the solution of inverse scattering problems, support information is useful in order to reduce the degree of nonlinearity of the relationship among the data and the unknowns, as well as the overall computational burden. Moreover, by taking into account the spectral properties of the scattered fields, it can be helpful to reduce the effect of noise on data. Accordingly, a 3D inversion strategy in which one performs a preliminary estimation of the support of the targets is considered in this paper to process the experimental data provided by the Institut Fresnel of Marseille, France. In particular, the imaging problem is tackled in a step-wise fashion, in which one first pursues a morphologic characterization of the targets using a linear sampling method based procedure. Then, the retrieved support is exploited to 'filter' the data and, finally, in the quantitative characterization of the targets. This last step is performed by using the optimized contrast source extended Born inversion method wherein the estimated support is exploited in order to reduce both the investigated domain and the nonlinearity of the inverse problem. (literal)
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