Cross-range scaling for non-uniformly rotating targets by sharpness maximization

Abstract

Cross-range scaling is a crucial work to target recognition in inverse synthetic aperture radar (ISAR) systems. However, it is still challenging for maneuvering targets due to the time-varying Doppler history, which degrades the image as well. This paper presents a novel method to estimate the scaling factor by optimizing the image quality. One highlight of this work is the usage of Matching Fourier Transform (MFT), which coincides with the non-uniform rotation model or the variant Doppler. The backscattered reflectivity can be concentrated in MFT domain when the parametric transform is perfectly matched with the signal form. Thus another novelty lies in the sharpness maximization of the MFT image by iteratively compensating the range-dependent phase error joint with the image formation. The proposed scheme manages to output the scaling factor and enhanced images. To alleviate the influence of residual translation phase error on estimation, conventional autofocus methods are invoked during the iterations. Simulation and real-data results confirm the effectiveness of the proposed method.