Kazempourradi, Seyed Mahdi2016-04-212016-04-212014-012014-0128-01-2014http://hdl.handle.net/11693/28957Cataloged from PDF version of thesis.Includes bibliographical references (leaves 56-60).Thesis (M.S.): Bilkent University, Department of Electrical and Electronics Engineering, İhsan Doğramacı Bilkent University, 2014.We developed a method that incorporates an algebraic compression technique to accelerate the computation of multiple monostatic radar cross sections (RCSs) of arbitrary 3-D geometries. Since most radars rely on the backscattering from a target, computing the monostatic RCS (MRCS) is needed more often than the bistatic RCS. Computation of each MRCS value requires a separate solution, which may be costly depending on the size of the problem. The task becomes considerably harder when the goal is to compute multiple MRCS values with high angular resolution. The proposed technique compresses the excitation matrix using the adaptive cross approximation (ACA) algorithm in the rst step. A recompression is applied on the matrices obtained from ACA by utilizing the QR decomposition and computing the singular value decomposition in an e - cient manner. The solution of each excitation is accelerated by the multilevel fast multipole algorithm. The numerical results demonstrate the e ciency and accuracy of our proposed method.xv, 60 leaves : graphics, tables.Englishinfo:eu-repo/semantics/openAccessAdaptive cross approximation(ACA)Multilevel fast multipole algorithm(MLFMA)Radar cross section(RCS)RecompressionThesisB130879