Compressed sensing technique for circular SAR imaging

Compressed sensing (CS) has been receiving a lot of interest because it provides possibilities to reconstruct signals or images from significantly fewer samples than Nyquist theorem acquire. In this paper, we apply this technique to circular SAR (CSAR). We demonstrate that CS has the potential to make two significant improvements to CSAR imaging: (i) reducing the number of samples to save memory and reduce data storage requirements, and (ii) suppressing the sidelobes in CSAR imaging to provide high image quality. The performance of CS technique is analysed through simulations.