A novel sparse synthetic aperture radar unambiguous imaging method based on mixed-norm optimization

Compared with traditional matched filtering (MF) based methods, sparse synthetic aperture radar (SAR) imaging could obtain high-quality images of sparse surveillance regions from down-sampled echo data. However, sparse SAR imaging still faces several challenges, especially in the fast recovery of large-scale scene and azimuth ambiguity suppression.