Efficient Sampling Method for 2D-Bistatic RCS Measurement using Cylindrical Near-Field to Far-Field Transformation and Iterations by Gaussian Process Regression

The near-field to far-field transformation method is highly accurate for measuring 2D bistatic RCS patterns but requires time-consuming near-field measurements at intervals satisfying the sampling theorem. This paper proposes a more efficient method for measuring the 2D bistatic RCS pattern of a metal flat plate using Gaussian process regression and cylindrical near-field to far-field transformation. The study found that non-uniform sampling and GPR iteration can achieve efficient sampling in cylindrical near-field to far-field transformation with GPR interpolation.