A partial rotation formulation of the circular near-field-to-far-field transformation (CNFFFT)

For many years now, General Dynamics has described the development, characterization, and performance of an image-based circular near-field-to-far-field transformation (CNFFFT) for predicting far-field radar cross sections (RCS) from near-field measurements collected on a circular path around the target. In this paper, we consider the CNFFFT algorithm as an azimuthal-filtering process, and develop a formulation capable of transforming data that is not measured over a full 360 degrees. Such a formulation has applications in measurement scenarios where collection of a complete rotation is not practical. As part of the development, we provide guidelines for the near-field data support required to achieve a desired accuracy in the sub-360 degrees CNFFFT result. Numerical simulations are provided to demonstrate that the results of this partial-rotation formulation are consistent with the full-circle CNFFFT results presented in past papers.