In this paper, a dual-model based adaptive sampling method is proposed for the fast calculation of broadband electromagnetic scattering. The difference between the rational function model (RFM) and cubic-spline (CS) based polynomial model issued to generate new frequency samples adaptively. Then, the cubic Hermite interpolation is used to approximate the final broadband RCS curve. The radar cross section (RCS) at each frequency sample is computed by the method of moment (MoM) which is accelerated by the adaptive cross approximation (ACA). Numerical results demonstrate that the proposed method is able to obtain the broadband RCS curve with high accuracy and reduce the computation time significantly. Compared with the method of moment and adaptive cross approximation method, the adaptive algorithm improves the computational efficiency by 77.13% in the sphere case, 83.79% in the rail model and nearly 90.72% in the missile example. In addition, the method proposed in this paper has the characteristics of nonuniform sampling and strong applicability and flexibility, which is able to combine other matrix compressed methods to effectively solve problems in electromagnetic field.
"Combination of Dual-Model-Base Adaptive Sampling Algorithm and Adaptive Cross Approximation for Fast Computation of Broadband RCS," Progress In Electromagnetics Research M,
Vol. 107, 65-77, 2022. doi:10.2528/PIERM21111205
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