A Novel SAR Imaging Algorithm Based on Compressed Sensing

To reduce the amount of measurements, compressed sensing (CS) has been introduced to synthetic aperture radar (SAR). In this letter, a novel CS-SAR imaging algorithm is proposed, which consists of 2-D undersampling, range reconstruction, range-azimuth decoupling, and azimuth reconstruction. In the proposed algorithm, the range profile is reconstructed in the fractional Fourier domain, and range-azimuth decoupling in the case of azimuth undersampling is realized by using the reference function multiplication and chirp-z transform. Comparisons with the existing 2-D undersampling CS-SAR imaging algorithms are also presented. Experimental results from both simulated and real data demonstrate that the proposed algorithm can efficiently realize high-quality imaging with limited measurements.