Sparse aperture wide-angle inverse synthetic aperture radar imaging based on compressive sensing

摘要

In high-resolution inverse synthetic aperture radar (ISAR) imaging, if the authors enlarge observation angle, range migration would appear and that can cause defocus problem. For full aperture data, the authors can use keystone transform to mitigate the range migration. However the keystone transform is difficult to directly applied in azimuth sparse sampled data. In this article, for azimuth sparse sampled data, the authors analyse the echo model and devise an algorithm based on compressive sensing theory to reconstruct scatters in high-resolution ISAR image. Simulation results demonstrate the validity of the method proposed in the article.