An Efficient ISAR Imaging and Scaling Method for Highly Maneuvering Targets Based on ICPF-PSVA

The imaging quality and efficiency are equally important in inverse synthetic aperture radar (ISAR) imaging. The high-order spatial variant (SV) phase errors induced by the target’s nonuniform rotational motion would seriously defocus the ISAR imaging results. The focused image can be obtained by exhaustive parameters estimation or optimization processing. However, the high-computational complexity limits its application in real-time imaging. To overcome this constraint, we propose an efficient ISAR imaging and scaling method for highly maneuvering targets by the integration of integrated cubic phase function (ICPF) and parametric spatial variant autofocus (PSVA) in this article. A novel rotational motion parameter estimation method based on ICPF, which only utilizes second-order phase term coefficients, is presented. Then, a parametric global model is established, which can achieve spatial variant (SV) autofocusing of defocused images based on estimated rotational motion parameters. Meanwhile, the cross-range scaling can also be realized using estimated effective rotational velocity (ERV). Without exhaustive parameters estimation and optimization search, the proposed ICPF-PSVA method not only achieves high-precision ISAR imaging but is also computationally efficient compared with the existing methods. Experiments using simulation data and measured data confirm the high efficiency of the proposed method in generating focused images of maneuvering targets.