volume | PIER Journals

Abstract

While analyzing wideband electromagnetic scattering problems using ultra-wideband characteristic basis function method (UCBFM), the reconstruction of a reduced matrix and the recalculation of an impedance matrix at each frequency point cost a large amount of time. To overcome this issue, a novel method that combines UCBFM with compressive sensing (CS) is proposed in this paper to rapidly analyse the wideband RCS. The proposed method makes the ultra-wide band characteristic basis functions (UCBFs) generated at the highest frequency as the sparse basis, introduces the CS theory, randomly extracts several rows from the original matrix as the measurement matrix, utilizes the corresponding excitation vector as the measurement value, and then employs the recovery algorithm, through which the solution of target induced current can be obtained. Due to partial filling of impedance matrix and efficient recovery algorithm, the wideband RCS computation time of the object is significantly reduced using the proposed method. Furthermore, the numerical simulation results show that the computation efficiency for the target wideband RCS can be further enhanced compared with that of the stand-alone UCBFM.

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Professor Zhonggen Wang

Dr. Chenwei Li

Dr. Yufa Sun

Professor Wenyan Nie

Dr. Pan Wang

Professor Han Lin