Near-field to far-field radar cross section transform incorporating super-resolution imaging with MUSIC

Near-field to far-field radar cross section transform techniques are of interest to permit an accurate radar scattering characterization of an object without the burden of a far-field measurement. To improve accuracy and target applicability, the transform developed in this report uses an original implementation of two-dimensional, near-field imaging with the Multiple Signal Classification (MUSIC) algorithm to precisely locate individual scattering centers. With the accuracy afforded by MUSIC, the spectral responses of the individual sources are readily characterized with a least squares algorithm and coherently summed to synthesize a far-field estimate. Rigorous theoretical development details and computational implementation considerations of the new transform are provided in advance of test results validating its usefulness with a variety of targets. Limitations of the super-resolution based near-field to far-field transform are identified and recommendations to enhance its performance close the report.