ISAR Imaging and Cross-Range Scaling for Maneuvering Targets by Using the NCS-NLS Algorithm

The azimuth resolution of an inverse synthetic aperture radar (ISAR) image is determined by the angular diversity of the target. In order to improve the azimuth resolution of an ISAR image, it is necessary to view the target at more different aspect angles, which is commonly achieved by extending the coherent processing interval (CPI). However, as the CPI lengthens, the effective rotation of a target can no longer be approximated to be uniform and the rotational acceleration should be taken into consideration. The non-uniform rotation can bring about the 2-D space-variant phase error, which degrades the focusing quality of an ISAR image seriously. In this paper, a novel ISAR imaging and a cross-range scaling algorithm for a maneuvering target with a non-uniform rotation are proposed. In the proposed algorithm, the spatially variant phase error is compensated for by the joint phase error compensation method based on nonlinear chirp scaling (NCS) principle. The estimation of the effective rotational information required in the NCS-based joint phase error compensation method and the cross-range scaling is transformed into a nonlinear least-squares (NLS) problem. The NLS problem is solved by Gauss–Newton method and FFTs with high efficiency. The results acquired from the processing of both the simulation and real data validate the effectiveness of the proposed algorithm.