High-Resolution Terahertz ISAR Imaging for Space Targets via Sidelobe Suppression and Subaperture Stitching

Terahertz (THz) inverse synthetic aperture radar (ISAR) imaging technology has demonstrated significant advantages in the field of high-resolution imaging of space targets. The large bandwidth and high carrier frequency characteristics of THz radar enable sub-centimetre resolution and all-weather space situational awareness (SSA) capability. However, due to the severe non-linearity of frequency sweeping and power unevenness of the broadband transmission signal of THz radar, as well as the complex scattering characteristics of the target, severe sidelobes and spurious signals appear in the images. Consequently, the performance of traditional window filtering or adaptive sidelobe reduction (ASR) algorithms is significantly reduced, or even fails. Furthermore, the imaging results of THz radar on space targets show inherent sparsity, and the main body of the space target obscures other components, which is not conducive to manual interpretation and automatic recognition. To address these challenges, this paper proposes a space target THz-ISAR imaging framework that combines sidelobe suppression and subaperture stitching. Firstly, a modified quasi-Newton minimum entropy algorithm (MQN-MEA) is designed to estimate the rotation parameters of the target, and the focusing imaging results are obtained after compensating for the phase error. Based on the estimated rotation parameters, the subaperture THz-ISAR images are matched. By exploiting the distributional differences between the mainlobe and sidelobes in the matched subaperture images, the sidelobes are effectively separated and suppressed. After subaperture image stitching, a high-resolution imaging result of the space target can be obtained. Finally, the superiority of the proposed method is verified by simulation data and outfield measurement data, and the enormous potential of THz radar technology for space target imaging is demonstrated.