Super-Resolution ISAR Imaging by Sequential Sparse Recovery.

Inverse synthetic aperture radar (ISAR) imaging needs a long coherent processing interval (CPI) to obtain high cross-range resolution. However, the Doppler frequency is time-varying for a maneuvering target, which will produce blurred ISAR image in a long CPI. In this article, we focus on super-resolution ISAR imaging during an adaptive short CPI by using sequential sparse recovery. To enhance the performance of SSL0, a regularized SSL0 (Re-SSL0) and an entropy-based stopping rule are presented. Besides, KT-based MTRC compensation, SVD-based dictionary whitening and rotation correlation-based cross-range scaling are introduced into the processing scheme. The superiority of the proposed method is validated by the experimental results based on simulated data.