A fast solution to monostatic RCS based on SVD-CBFM and RACA

An efficient method was proposed to solve monostatic RCS based on singular value decomposition-characteristic basis function method (SVD-CBFM). To reduce the numbers of incident wave excitations, the method considers the coupling effect among the sub-blocks, and calculates the secondary characteristic basis function (SCBF) of each sub-block. The recompressed adaptive cross approximation (RACA) algorithm was applied to recompress the characteristic basis functions (CBFs), which can accelerate the generation of CBFs. In order to further improve the speed of the matrix vector multiplication in the construction process of the SCBF and reduced matrix, the RACA algorithm was also applied to fill the impedance matrix of the far field. The numerical examples demonstrate the accuracy and efficiency of the proposed method.