Large-Scale Characteristic Mode Analysis With Fast Multipole Algorithms

被引:39
作者
Dai, Qi I. [1 ]
Wu, Junwei [2 ]
Gan, Hui [1 ]
Liu, Qin S. [3 ]
Chew, Weng Cho [1 ]
Sha, Wei E. I. [3 ]
机构
[1] Univ Illinois, Dept Elect & Comp Engn, 1406 W Green St, Urbana, IL 61801 USA
[2] Wuhan Univ, Sch Elect & Informat, Wuhan 430072, Hubei, Peoples R China
[3] Univ Hong Kong, Dept Elect & Elect Engn, Pokfulam, Hong Kong, Peoples R China
基金
美国国家科学基金会;
关键词
Augmented electric field integral equation; characteristic mode; combined field integral equation; fast multipole algorithm (FMA); large scale; FIELD INTEGRAL-EQUATION; ELECTROMAGNETIC SCATTERING; CONDUCTING BODIES; COMPLEX;
D O I
10.1109/TAP.2016.2526083
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Large-scale characteristic mode analysis (CMA) poses challenges in computational electromagnetics as it calls for efficient solutions of large dense generalized eigenvalue problems. In this paper, we consider two applications that involve large-scale CMA, and demonstrate that fast multipole algorithms (FMAs) can be easily incorporated into the implicitly restarted Arnoldi method (IRAM) for eigenanalysis after simple modifications. The first application performs CMA for large platforms made by closed perfectly conducting surfaces. Multilevel FMA (MLFMA) is embedded into a combined field integral equation-based theory of characteristic mode (TCM). The second application addresses multiscale modeling of small but geometrically complicated objects, which possess fine subwavelength structures. An augmented electric field integral equation-based TCM is formulated, and low-frequency (LF-) FMA is adopted to accelerate the required matrix-vector products.
引用
收藏
页码:2608 / 2616
页数:9
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