ISAR Imaging Method for High-speed Maneuvering Target Based on MFT-UNET3+ Network

When inverse synthetic aperture radar (ISAR) images a high-speed maneuvering target, the imaging results of traditional methods are blurred and defocused in the range and azimuth directions because of the high speed and acceleration of the target. The existing imaging methods of maneuvering targets have poor imaging effects or low efficiency, and can’t eliminate the migration through range cells (MTRC) of far points on the target. Given that the existing methods can’t meet the imaging requirements of high-speed maneuvering targets, a new method by combing the UNET3+ convolution neural network (CNN) to machting Fourier transform (MFT) imaging process is proposed in this paper. Overcoming the limitations of the existing imaging methods, the proposed method can realize fast and accurate imaging for high-speed maneuvering targets. Experiments show that the novel MFT-UNET3+ method can achieve a good focus even under the condition of a low signal-to-noise ratio and down-sampling.