High-Precision ISAR Imaging of Translational Target Using Subaperture Segmentation and Motion Reconstruction

High-precision imaging with inverse synthetic aperture radar (ISAR) is essential for effective target recognition. However, the extended coherent processing interval (CPI) and the small size of resolution cells increase the complexity of motion compensation. Traditional techniques fail to adaptively compensate for the pose aliasing in translational targets, resulting in suboptimal imaging quality. To address this challenge, this article proposes a novel high-precision ISAR imaging method that leverages subaperture segmentation and motion reconstruction. Initially, a parallel generalized Radon-Fourier transform (GRFT) is employed to adaptively segment subapertures of nonuniform lengths and estimate the radial motion parameters within each subaperture; thus, achieving radial motion compensation. Subsequently, range-Doppler (RD) image registration and the quality of back-projection images are utilized to sequentially estimate the equivalent rotational velocity. By integrating the estimated motion parameters, a precisely focused ISAR image can be obtained. The effectiveness of the proposed method is validated through centimeter-level resolution imaging, demonstrating significant improvements in imaging performance.