A super-resolving imaging algorithm of forward-looking SAR based on compressive sensing

As having the imaging ability of area in front of flight direction, forward-looking synthetic aperture radar (SAR) has become a hot topic in areas of SAR research. Nevertheless, the currently exploited imaging algorithms of forward-looking SAR suffer from poor azimuth resolution induced by limited azimuth aperture length. To address this challenge, we develop a super-resolving imaging algorithm for forward-looking SAR based on compressive sensing theory. Firstly, the spatial geometry and signal model of forward-looking SAR is analyzed. After that, the compressive sensing theory is introduced to improve azimuth resolution. Imaging simulations based on Ku-band image data from the MiniSAR system demonstrate the effectiveness of the proposed method.