Enhancement of stepped-frequency SAR imaging based on compressive sensing

In this paper, a novel CS imaging framework is proposed for the purpose of improving the imaging performance of stepped frequency synthetic aperture radar (SAR). Meanwhile, a super-resolving imaging algorithm is proposed based on the nonquadratic optimization technique. Simulated and rail SAR measured data are applied to demonstrate the efficiency of the novel framework with proposed super-resolving algorithm. Experimental results validate the superiority of this method over previous approaches in terms of robustness in low SNR, better super-resolving ability and improved imaging performance in complex scene.