2012
DOI: 10.1109/tgrs.2012.2184291
|View full text |Cite
|
Sign up to set email alerts
|

A Robust Preconditioned GMRES Method for Electromagnetic Scattering From Dielectric Rough Surfaces

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1

Citation Types

0
3
0

Year Published

2013
2013
2020
2020

Publication Types

Select...
7

Relationship

3
4

Authors

Journals

citations
Cited by 9 publications
(3 citation statements)
references
References 38 publications
0
3
0
Order By: Relevance
“…For Fig. 5(a), φ s = 0.9476, a max = 0.0782, tan δ = 0.4112, Next, we incorporate the proposed method with the efficient and robust right-preconditioned generalized minimal residual (GMRES-RP) method [4] to analyze electromagnetic scattering from rough surfaces. A diagram is shown in Fig.…”
Section: Resultsmentioning
confidence: 99%
“…For Fig. 5(a), φ s = 0.9476, a max = 0.0782, tan δ = 0.4112, Next, we incorporate the proposed method with the efficient and robust right-preconditioned generalized minimal residual (GMRES-RP) method [4] to analyze electromagnetic scattering from rough surfaces. A diagram is shown in Fig.…”
Section: Resultsmentioning
confidence: 99%
“…In this method, a right preconditioned generalized minimal residual (GMRES-RP) [11] method with the forward-backward method (FBM) [12], is combined with the spectral acceleration (SA) [13], [14] technique to expedite the computation of matrix-vector product. Although this method was originally designed for terrain surfaces, there is no difficulty in extending it to the composite ocean surface.…”
Section: Introductionmentioning
confidence: 99%
“…Recently we have developed a highly efficient and robust numerical method for the analysis of scattering from randomly rough surfaces. In this method, a generalized minimal residual procedure which is right preconditioned (GMRES-RP) [14] with the forward-backward method (FBM) [15], in combination with the spectral acceleration (SA) [16,17] technique to expedite the computation of matrix-vector product. The applied preconditioning is found to transform the original linear system from near singular to stable with a good condition number; specifically, the spectrum of the preconditioned matrix is found condensed in the vicinity of the point 1 in the complex plane, an indicator of the good approximation quality of the preconditioner to the original matrix.…”
Section: Introductionmentioning
confidence: 99%