A novel SAR imaging algorithm based on compressed sensing

High speed A/D sampling and large scale data storage are two basic challenges of the high resolution SAR system. The developing of radar system is limited by these two challenges under the Nyquist sampling theory. Compressed sensing (CS) is a new approach of sparse signals recovered beyond the constraints of Nyquist sampling technique. With the consideration of these problems that might happen and the advantage of CS theory, a novel SAR image processing algorithm based on compressive sensing was proposed in this paper. Using the data whose sampling rate is lower than the required Nyquist sampling rate, the CS-based algorithm operates at range and azimuth dimensional respectively. Experimental results show the presented algorithm based on compressed sensing have a better performance than the conventional SAR algorithm even with only smaller samples, and also indicate that the presented algorithm is robustness with existence of serious noise.