Numerical Methods to Solve the Problem of Scattering from Electrically Large Bodies.

Abstract

An alternative to directly inverting the large MoM matrix is to recast the problem in a form that is suitable for solution via iterative schemes. Although the use of iterative methods may enable one to treat scatterers that are an order of magnitude larger electrically, a close examination of them shows that most of them are not well-suited for handling multiple excitations in an efficient manner. In this report some variational-iteration schemes based on the use of prechosen entire domain basis functions that are suitable not only for treating larger bodies but for handling multiple incident angles as well are suggested. It is shown that, for this type of variational iteration schemes, the choice of an initial guess plays an important role in achieving a rapid convergence. Also, in an effort to further improve the convergence, a hybrid technique, where the method of moments is utilized to generate better gradient vectors in the iterative procedure, is developed. A simple case of scattering from a perfectly conducting or resistively-loaded strip is use to demonstrate the effectiveness of the methods. Keywords: Electromagnetic scattering, Iterative methods, Radar cross sections, and Resistive strips. (KR)

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1988
Accession Number
ADA198098

Entities

People

  • A. S. Chang
  • Raj Mittra

Organizations

  • University of Illinois Urbana–Champaign

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Classification
  • Convergence
  • Convolution Integrals
  • Coordinate Systems
  • Electric Fields
  • Electromagnetic Scattering
  • Equations
  • Excitation
  • Far Field
  • Geometry
  • Integral Equations
  • Iterations
  • Method Of Moments
  • Plane Waves
  • Scattering
  • Security
  • Traveling Waves

Readers

  • Electromagnetic Wave Scattering and Antenna Radiation Engineering
  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)