QR-AMCBFM技术快速分析电磁散射特性

Hybrid Adaptively Modified Characteristic Basis Function and QR Factorization Algorithm for Fast Analyzing Electromagnetic Scattering

  • 摘要: 提出了一种新的特征基函数法——自适应修正特征基函数法(AMCBFM),并将其与基于dual-MGS的QR分解技术结合,构造一种新的混合方法——QR-AMCBFM。该方法基于对目标体分块,并按一定的距离关系划分为近、远场两部分,用AMCBFM计算出每一块上的初阶电流。在计算高阶电流时,先对块间互阻抗矩阵进行QR分解以决定远场区的互阻抗可否舍弃;然后计算出高阶基函数以及电流系数。数值结果表明,QR-AMCBFM技术具有相当高的计算效率。

     

    Abstract: A daptively modified characteristic basis function method (AMCBFM) based on QR factorization with a dual modified Gram-Schmidt (dual-MGS) algorithm called QR-AMCBFM is proposed. In this hybrid method, the object geometry is partitioned into distinct blocks, which are divided into near and far groups depending on distances. The primary basis functions are derived firstly. In order to get the high-level basis functions, QR factorization algorithm based on dual-MGS is applied to decompose the mutual coupling matrixes to decide that the rest interactions arising in farther blocks are ignored or not. Subsequently, the high-level characteristic basis functions and the coefficient of current are calculated. Results show that the QR-AMCBFM can solve the problems very efficiently.

     

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