TWO-LEVEL PRECONDITIONING TECHNIQUE BASED ON SPARSE RECURSIVE CHOLESKY FACTORIZATION FOR FAST MONOSTATIC RCS COMPUTATION

摘要

An efficient two-level preconditioning technique based on sparse recursive Cholesky factorization (SRCF) is proposed to solve linear equations in monostatic radar cross section computation. The SRCF preconditioner is used as the first level preconditioning, and a spectral preconditioner, constructed from the eigenvectors of the SRCF preconditioned system, is adopted as the second level preconditioning. The resultant linear systems are solved by restarted generalized minimal residual method. Multilevel fast multipole algorithm is implemented to accelerate computation and reduce memory requirement. Numerical results demonstrate the proposed method is efficient in reducing the number of matrix-vector product, and speed-up factors of 4.26 and 5.89 are observed for electromagnetic scattering by a perfect electric conductor almond and a civil aircraft model, respectively.