Improved SAI Preconditioning of Hybridized MLFMA for Electrically Large Multiscale Problems

Sparse approximate inverse (SAI) preconditioner is frequently used to speed up the iteration of fast multipole algorithm when solving electrically large problems. However, its efficiency is unsatisfactory when applied to hybrid fast algorithms for electrically large multiscale problems. In this letter, a fast reconstruction SAI (FRSAI) preconditioner is introduced to improve the convergence of linear equation systems for solving electrically large multiscale problems. The performance of the novel FRSAI preconditioner is illustrated using numerical examples of complex electromagnetic scattering and radiation problems.