A novel method of constructing measurement matrix for CS-based SAR imaging

Compressed sensing (CS) is a recently developed theory which allows reconstruction of sparse signals with a number of measurements much lower than that required by the Nyquist sampling. The theory has been applied in many areas within synthetic aperture radar (SAR). This paper presents a novel method of constructing measurement matrix for CS-based SAR imaging, which enables the sensing matrix to meet RIP with high probability. Simulated results demonstrate the effectiveness of the proposed method, which can obtain a high quality radar image with fewer data samples, and the advantage of the proposed method is more obvious especially at high noise levels.