• DocumentCode
    2676311
  • Title

    Inverse scattering for shape and conductivity

  • Author

    Chien, Wei ; Chin, Chien Ching

  • Author_Institution
    Dept. of Electr. Eng., Tamkang Univ., Taipei, Taiwan
  • fYear
    2003
  • fDate
    Oct. 28 2003-Nov. 1 2003
  • Firstpage
    441
  • Lastpage
    444
  • Abstract
    We consider the inverse problem of determining both the shape and the conductivity of a two-dimensional conducting scatterer from a knowledge of the far-field pattern of TM waves by solving the ill posed nonlinear equation. Based on the boundary condition and the measured scattered field, a set of nonlinear integral equations is derived and the imaging problem is reformulated into an optimization problem. Satisfactory reconstructions have been achieved by the genetic algorithm. Numerical results demonstrated that, even when the initial guess is far away from the exact one, good reconstruction has been obtained. Numerical results show that multiple incident directions permit good reconstruction of shape and conductivity.
  • Keywords
    conducting bodies; electromagnetic wave scattering; genetic algorithms; integral equations; inverse problems; nonlinear equations; TM waves; boundary condition; conductivity reconstruction; far-field pattern; genetic algorithm; ill posed nonlinear equation; imaging problem; inverse scattering; multiple incident directions; nonlinear integral equations; optimization problem; satisfactory reconstructions; shape reconstruction; two-dimensional conducting scatterer; Conductivity; Current density; Electromagnetic scattering; Genetic algorithms; Image reconstruction; Integral equations; Inverse problems; Nonlinear equations; Shape; Surface impedance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Antennas, Propagation and EM Theory, 2003. Proceedings. 2003 6th International SYmposium on
  • Conference_Location
    Beijing, China
  • Print_ISBN
    0-7803-7831-8
  • Type

    conf

  • DOI
    10.1109/ISAPE.2003.1276722
  • Filename
    1276722