Title :
A Novel Hierarchical Two-Level Spectral Preconditioning Technique for Electromagnetic Wave Scattering
Author :
Ding, Dazhi Z. ; Chen, Ru-Shan ; Fan, Z.H. ; Rui, P.L.
Author_Institution :
Nanjing Univ. of Sci. & Technol., Nanjing
fDate :
4/1/2008 12:00:00 AM
Abstract :
A new set of higher order hierarchical basis functions based on curvilinear triangular patch is proposed for expansion of the current in electrical field integral equations solved by method of moments. The hierarchical two-level spectral preconditioning technique is developed for the generalized minimal residual iterative method, in which the multilevel fast multipole method is used to accelerate matrix-vector product. The sparse approximate inverse (SAI) preconditioner based on the higher order hierarchical basis functions is used to damp the high frequencies of the error and the low frequencies is eliminated by a spectral preconditioner in a two-level manner defined on the lower order basis functions. The spectral preconditioner is combined with SAI preconditioner to obtain a hierarchical two-level spectral preconditioner. Numerical experiments indicate that the new preconditioner can significantly reduce both the iteration number and computational time.
Keywords :
approximation theory; electric field integral equations; electromagnetic wave scattering; iterative methods; matrix algebra; method of moments; vectors; curvilinear triangular patch; electrical field integral equations; electromagnetic wave scattering; generalized minimal residual iterative method; hierarchical two-level spectral preconditioning technique; higher order hierarchical basis functions; matrix-vector product; method of moments; multilevel fast multipole method; sparse approximate inverse preconditioner; Acceleration; Current distribution; Electromagnetic scattering; Finite element methods; Frequency; Integral equations; Iterative methods; Moment methods; Shape; Sparse matrices; Electromagnetic scattering; generalized minimal residual (GMRES) algorithm; multilevel fast multipole method (MLFMM); preconditioning techniques; sparse approximate inverse (SAI);
Journal_Title :
Antennas and Propagation, IEEE Transactions on
DOI :
10.1109/TAP.2008.919188