The invention relates to a
radar cross section test method based on
deep learning and ISAR imaging inversion, and the method comprises the steps: employing an ISAR imaging test mode to obtain
broadband radar scattering echo signals of a target and a calibration body, carrying out the calibration
processing, and carrying out the ISAR imaging through employing a filtering-
inverse projection imaging algorithm, and accurately extracting an ISAR image scattering
signal region by using the trained
deep learning model, inverting and reconstructing an RCS value with high precision by using an FFT (
Fast Fourier Transform)-interpolation integral ISAR imaging inversion
algorithm, and traversing by changing an ISAR imaging aperture center
azimuth angle to obtain target omni-directional angle RCS data. According to the
radar cross section test method based on
deep learning and ISAR imaging inversion provided by the invention, the test practice problems of accurate extraction of an ISAR image scattering region, high-precision inversion reconstruction of the RCS by the ISAR image and the like are solved, and an RCS
data acquisition method is expanded.