Radar Imaging Through a Building Corner (Articolo in rivista)

  • Radar Imaging Through a Building Corner (Articolo in rivista) (literal)
  • 2014-01-01T00:00:00+01:00 (literal)
  • 10.1109/TGRS.2014.2301882 (literal)
Alternative label
  • Gennarelli, Gianluca; Riccio, Giovanni; Solimene, Raffaele; Soldovieri, Francesco (2014)
    Radar Imaging Through a Building Corner
    in IEEE transactions on geoscience and remote sensing
  • Gennarelli, Gianluca; Riccio, Giovanni; Solimene, Raffaele; Soldovieri, Francesco (literal)
Pagina inizio
  • 6750 (literal)
Pagina fine
  • 6761 (literal)
  • 52 (literal)
  • 12 (literal)
  • 10 (literal)
  • ISI Web of Science (WOS) (literal)
  • Natl Res Council Italy; University of Salerno; Seconda Universita degli Studi di Napoli (literal)
  • Radar Imaging Through a Building Corner (literal)
  • Through-wall imaging (TWI) requires dealing with targets embedded in a complex obscuring environment such as the walls of a building. This obscuring layout is often composed by many simple elements (possibly interacting) such as slabs, corners, and T-like structures. Most of the existing literature on TWI has focused on slab-like walls, which is reasonable when the targets are relatively far from corners. This paper instead concerns the TWI in the more challenging situation where the targets are in close proximity (inside and/or outside) of a building corner. The aim is to gain insight into how propagation through the corner impacts on the imaging problem. To keep the study simple, a preliminary analysis is presented for a 2-D geometry under the linearized Born approximation. First, the Green's function, as well as the kernel of the relevant scattering operator, is evaluated by using a high-frequency analytical approach based on the geometrical optics and the uniform theory of diffraction. This allows one to take into account the multipath propagation phenomena and provide thus an expression of the scattering operator more accurate than that viable under the assumption of a simple slab wall. Then, the imaging is achieved by solving the relevant linear inverse scattering problem with a regularizing truncated-singular-value-decomposition algorithm. The filtering introduced by the inversion procedure, which is dependent on the considered background scenario, is highlighted and linked to the achievable performance while imaging targets both internal and external with respect to the corner. Finally, reconstruction results obtained from synthetic data are reported to assess the approach. (literal)
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