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Fast Numerical Algorithms for 3-D Scattering from PEC and Dielectric Random Rough Surfaces in Microwave Remote Sensing.

机译:微波遥感中PEC和介电随机粗糙表面3-D散射的快速数值算法。

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摘要

We present fast and robust numerical algorithms for 3-D scattering from perfectly electrical conducting (PEC) and dielectric random rough surfaces in microwave remote sensing. The Coifman wavelets or Coiflets are employed to implement Galerkin's procedure in the method of moments (MoM). Due to the high-precision one-point quadrature, the Coiflets yield fast evaluations of the most off-diagonal entries, reducing the matrix fill effort from O(N2) to O( N). The orthogonality and Riesz basis of the Coiflets generate well conditioned impedance matrix, with rapid convergence for the conjugate gradient solver. The resulting impedance matrix is further sparsified by the matrix-formed standard fast wavelet transform (SFWT). By properly selecting multiresolution levels of the total transformation matrix, the solution precision can be enhanced while matrix sparsity and memory consumption have not been noticeably sacrificed. The unified fast scattering algorithm for dielectric random rough surfaces can asymptotically reduce to the PEC case when the loss tangent grows extremely large. Numerical results demonstrate that the reduced PEC model does not suffer from ill-posed problems. Compared with previous publications and laboratory measurements, good agreement is observed.
机译:我们提出了用于微波遥感中来自完美导电(PEC)和电介质随机粗糙表面的3-D散射的快速而强大的数值算法。使用Coifman小波或Coiflets来实现矩量法(MoM)中的Galerkin程序。由于具有高精度的单点正交,因此Coiflet可以对大多数非对角线条目进行快速评估,从而将矩阵填充工作量从O(N2)减少到O(N)。 Coiflet的正交性和Riesz基产生条件良好的阻抗矩阵,并且对于共轭梯度求解器具有快速收敛性。所得的阻抗矩阵通过矩阵形成的标准快速小波变换(SFWT)进一步稀疏。通过适当选择总转换矩阵的多分辨率级别,可以提高解决方案的精度,同时不会显着牺牲矩阵稀疏性和内存消耗。当损耗角正切极大时,用于电介质随机粗糙表面的统一快速散射算法可以渐近地简化为PEC情况。数值结果表明,简化后的PEC模型不会出现不适的问题。与以前的出版物和实验室测量值相比,观察到了很好的一致性。

著录项

  • 作者

    Zhang, Lisha.;

  • 作者单位

    Arizona State University.;

  • 授予单位 Arizona State University.;
  • 学科 Electromagnetics.;Remote sensing.
  • 学位 Ph.D.
  • 年度 2016
  • 页码 113 p.
  • 总页数 113
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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