A novel imaging method for random stepped frequency SAR with low SNR

This letter proposes a novel structured compressive sensing (CS) imaging method in random stepped frequency (RSF) synthetic aperture radar (SAR) for better imaging performance in the presence of strong additive noise. In this method, the multiple measurement vectors (MMV) model is established in range-Doppler domain with range migration taken into consideration and a modified sparse recovery algorithm is derived to synthesize the one-dimension range profile. Traditional cross-range focusing algorithm is then performed to obtain a well-focused image. The proposed method makes full use of the coherent information among different bursts, which may further illuminate the influence of additive noise and decrease the number of transmitted pulses needed in one burst. The simulated results demonstrate the validity of the proposed method.