Adaptive compressed sampling technique for efficient calculation of monostatic scattering

An adaptive compressed sampling method is proposed to reduce the time requirement for computation of monostatic scattering. The angular samples that would be most informative can be selected optimally by using cubic-spline interpolation method. In contrast to our previous work, adaptive sampling is applied to choose the key excitation vectors instead of electric current vectors. Reduction of the number of multiple excitation vectors can lead to significantly reduced computation time. Moreover, with low-rank property, the excitation vectors at these sampling angles may be further compressed by singular value decomposition (SVD), resulting in a more efficient adaptive sampling method. SVD can be replaced by an adaptive cross algorithm to further reduce the computational complexity. Numerical results demonstrate that this method is efficient for monostatic radar cross section (RCS) calculation with high accuracy.