A Surrogate Modeling Technique Based on Space Mapping for Radar Cross Section

A novel surrogate model is proposed based on space mapping to maintain accurate predictions of the radar cross section over a relative large range of frequencies. With a sparse-sample full-wave solver and a dense-sample ray-tracing solver, the surrogate model can be established with a small computational burden. A mapping function is introduced to represent the relationship between two such solvers to overcome the limitations of the conventional fixed linear mapping form. Two numerical examples are used to verify the effectiveness of the proposed method, which demonstrate its ability to achieve an ideal accuracy with limited computational resources.