• DocumentCode
    247833
  • Title

    Fast computing of large 3D dielectric forest scattering problems using the Characteristic Basis Function Method with the Adaptative Cross Approximation algorithm

  • Author

    Fenni, Ines ; Roussel, Helene ; Darces, Muriel ; Mittra, Raj

  • Author_Institution
    L2E, UPMC Univ. Paris 06, Paris, France
  • fYear
    2014
  • fDate
    6-11 July 2014
  • Firstpage
    2002
  • Lastpage
    2003
  • Abstract
    This paper presents the hybridation of the Characteristic Basis Function Method with the Adaptative Cross Approximation algorithm while generating the reduced linear equation system. The proposed method is applied to 3D scattering model in the context of forest remote sensing. It enables us to realize a significant improvement of the performances of the CBFM both in terms of memory use and CPU time while maintaining a good level of accuracy compared to the CBFM solution.
  • Keywords
    approximation theory; electromagnetic wave scattering; remote sensing; 3D scattering model; CBFM solution; CPU time; adaptative cross approximation algorithm; characteristic basis function method; forest remote sensing; large 3D dielectric forest scattering problems; reduced linear equation system; Algorithm design and analysis; Approximation algorithms; Approximation methods; Mathematical model; Method of moments; Scattering; Vegetation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Antennas and Propagation Society International Symposium (APSURSI), 2014 IEEE
  • Conference_Location
    Memphis, TN
  • ISSN
    1522-3965
  • Print_ISBN
    978-1-4799-3538-3
  • Type

    conf

  • DOI
    10.1109/APS.2014.6905328
  • Filename
    6905328