A strategy of SAR imaging based on 2-D block compressive sensing

For synthetic aperture radar (SAR) systems, high data rate is generally needed to achieve high-resolution of two dimension images, which leads to the huge amount of data storage. In the framework of compressive sensing theory, the compressibility of the signal makes it possible to reconstruct the signal from significantly reduced number of samples. And the radar data is proven to be compressible in most cases. In this study, a new SAR imaging scheme based on compressive sensing is proposed. This strategy performs range compression and azimuth compression simultaneously, and takes advantage of the correlation of the echo signals received in different azimuth positions. Moreover, this strategy does not need to perform Range Cell Migration. The computation complexity as well as the memory required is significantly reduced. Simulation experiments are carried out with additive noise, which imply the feasibility and advantages of the new strategy.