1998
DOI: 10.1029/98rs01888
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A novel acceleration algorithm for the computation of scattering from rough surfaces with the forward‐backward method

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Cited by 162 publications
(115 citation statements)
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“…(9). The criterions in selecting in C δ and implementing for the spectral integral have been well described in [6,10,3,23].…”
Section: The Saa Of Green's Functionmentioning
confidence: 99%
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“…(9). The criterions in selecting in C δ and implementing for the spectral integral have been well described in [6,10,3,23].…”
Section: The Saa Of Green's Functionmentioning
confidence: 99%
“…The operational counts is O(N 2 ) (of order N 2 ) and, thus, the simulation of quite large surfaces becomes possible, even for low grazing angle (LGA) incidence. The FBM for PEC rough surface has been accelerated by novel SAA first described in [3], and then implemented for both MFIE and electric field integral equation (EFIE) in [4]. The computational cost and storage requirements are further reduced to O(N ).…”
Section: Introductionmentioning
confidence: 99%
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“…The current induced on the strips is solved for using the method of moments and computed by standard iterative solvers such as the conjugate gradient (CG) or forward-backward method (F-BM) [Hottiday et at., 1996[Hottiday et at., , 1998]. At the core of the proposed approach a novel spectral algorithm (NSA), recently proposed by Chou and Johnson [1998] in the context of the computation of scattering from rough surfaces, is used to reduce the computational cost of the matrix-vector products involved in those algorithms to O(N).…”
Section: Valero and Rojas: Fast Solution For Large 2-d Microstrip Strmentioning
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%