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

Abstract

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.

Keywords

• image resolution
• radar imaging
• synthetic aperture radar
• radar resolution
• transforms
• compressed sensing
• image sampling
• image reconstruction
• range migration
• aperture data
• azimuth sparse sampled data
• compressive sensing theory
• high-resolution isar image
• high-resolution inverse synthetic aperture radar imaging
• observation angle
• sparse aperture wide-angle inverse synthetic aperture radar imaging
• defocus problem
• keystone transform
• full aperture data
• echo model
• scatter reconstruction