• DocumentCode
    690233
  • Title

    An adaptive facet subdivision scheme for the shadowing culling of large and complex targets

  • Author

    Song Shi ; Huafang Li ; Wei Pei ; Hui Gao ; Kobayashi, Hideo

  • Author_Institution
    Lab. of Electromagn. Technol., Beijing Municipal Inst. of Labor Protection, Beijing, China
  • fYear
    2013
  • fDate
    15-17 Nov. 2013
  • Firstpage
    205
  • Lastpage
    208
  • Abstract
    An adaptive facet subdivision scheme which is suitable for the shadow culling of large and complex objects is presented. Unlike the pre-meshing method by fine meshing the object to reduce the shadowing error; in the proposed scheme, the shadowing is culled by adaptively subdividing the triangular facets along the boundary of the shadow and no shadowing error remained. By applying the scheme recursively, beside the incident shadowing, the shadowing caused by any order multiple reflection can be calculated. The adaptive facet subdivision only occurs in the process of scattering electromagnetic field calculation, and the pre-meshing of the target surface is not necessary. The proposed scheme provides precisely facet subdivision, minimum computer resource requirements and convenient run-times.
  • Keywords
    electromagnetic wave scattering; radar cross-sections; RCS; adaptive facet subdivision; adaptive facet subdivision scheme; computer resource; facet subdivision; incident shadowing; premeshing method; radar cross section; scattering electromagnetic field calculation; shadow culling; target surface; triangular facets; Laboratories; Shadow mapping; Adaptive Facet Subdivision; Coordinate Transformation; Multiple Reflection; Physical Optics (PO); RCS prediction software; Radar Cross Section (RCS); Shadowing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronics Information and Emergency Communication (ICEIEC), 2013 IEEE 4th International Conference on
  • Conference_Location
    Beijing
  • Type

    conf

  • DOI
    10.1109/ICEIEC.2013.6835488
  • Filename
    6835488