Fast Solution of Wideband RCS Using UCBFM and Compressive Sensing

In the ultra-wide band characteristic basis function method (UCBFM) for the wideband electromagnetic scattering problems of electrically large objects, the impedance matrix calculation efficiency at single frequency point is low. A novel method combining UCBFM and compressive sensing (CS) is proposed in this paper to solve this problem. This method randomly extracts several rows of the original impedance matrix for filling as the measurement matrix, and the corresponding excitation vector as measured value. Therefore, the calculation speed of the impedance matrix can be improved. Then the wideband RCS can be constructed quickly and accurately with fewer measurements by the recovery algorithm. Numerical simulation results show that compared with UCBFM, the computational efficiency of target wideband RCS can be further improved.