Three-Dimensional Near-Field to Far-Field Transformation for Radar Cross Section Estimation of Elongated Targets via Subdimensional Hybrid Conversion

Abstract

Image-based (IB) near-field to far-field transformation (NFFFT) is a useful method for the valid prediction of radar cross sections (RCSs) from short-range monostatic measurements. Many previous studies on the IB NFFFT algorithm have been limited to two-dimensional (2D) measurement cases. In this work, a subdimensional hybrid conversion approach is proposed as a relevant three-dimensional (3D) NFFFT method consisting of the following procedures. First, the spherical-wave information collected through 3D scanning is converted to a cylindrical waveform by applying the 2D circular NFFFT (CNFFFT) method to every vertical subplane (r-θ plane). Then, a horizontal far-field radar image on the x-y plane and an RCS pattern are extracted through direct integration of a 2D focusing operator modified to compensate for a magnitude error through distance approximation during the CNFFFT procedure. The results of a comparative study with direct integration of a 3D focusing operator are presented to show the validity and performance of the proposed method.