Fast Analysis of Broadband Electromagnetic Scattering Problems by Combining Hyper Basis Functions-Based MoM With Compressive Sensing

The hyper basis functions (HBF)-based MoM has been proven to be an efficient numerical method to analyze broadband electromagnetic scattering problems. However, this method costs a lot of time to reconstruct the impedance matrix and reduced matrix at each frequency point. In order to solve the above problem, a novel method combining HBF-based MoM and compressive sensing (CS) has been proposed in this paper. The proposed method first applies the characteristic modes (CM) derived at the highest frequency point as the HBF for solving the scattering problems at lower frequency points, and performs sparse transform of the induced currents as the sparse basis for the CS framework. Then the measurement matrix is constructed using the method of uniformly extracting the impedance matrix by rows to obtain stable calculation results. Finally, according to the prior condition that a few CM are sufficient to characterize the surface currents approximately, the recovery algorithm is simplified least square method to reconstruct the current coefficients. Numerical simulation results show that it can significantly improve the efficiency of solving broadband electromagnetic problems compared with HBF-based MoM.