Three Dimensional Image-Based Radar Cross Section Extrapolation via Planar Projective Transforms

Conventional radar cross section (RCS) measurements require far-field or compact-antenna-test-range (CATR) conditions, which have strict restrictions and high implementation costs. By contrast, RCS extrapolation methods in the near zone are more convenient and practical, which become the research emphasis in recent years. This paper presents a novel RCS extrapolation method based on the combination of near-field 3D synthetic aperture radar (SAR) technique and planar projective transforms (PPT) algorithm. Firstly, to extract the target’s reflectivity distribution, we apply near-field 3D SAR imaging and obtain 3D near-field RCS (NFRCS) images. Secondly, to meet the requirement of RCS measurements, we derive a novel correction factor used to precisely expand 3D NFRCS images. Finally, we extrapolate the plane-wave responses in the azimuth-vertical dimensions, which presents as planar patterns. The proposed method utilizes the complete 3D image-based information to overcome the inherent constraints of classical RCS extrapolation methods on application scenarios, which has the advantages of broad applicability and high flexibility. The detailed derivation and implementation of this method are described in this paper. The simulation and experiment results verify that the proposed method can provide the equivalent CATR result within ±11° azimuth and elevation angles, and it is applicable to precisely measuring the point, surface, and complex scatterers.