Data Acquisition and Processing of Parallel Frequency Sar Based on Compressive Sensing

Traditional synthetic aperture radar (SAR) utilizes Shannon-Nyquist theorem for high bandwidth signal sampling, which induces a complicated SAR system, and it is difficult to transmit and process a huge amount of data caused by high A/D rate. Compressive sensing (CS) indicates that the compressible signal using a few measurements can be reconstructed by solving a convex optimization problem. A novel SAR based on CS theory, named as parallel frequencies SAR (PFSAR), is proposed in this paper. PFSAR transmits a set of narrow bandwidth signals which compose the large total bandwidth. Therefore, PFSAR only uses much less data to obtain a superiority image compared with a traditional SAR system. The data acquisition mode of PFSAR is developed and an algorithm of target scene reconstruction based on compressive sensing applied to PFSAR is proposed. The azimuth imaging of PFSAR is carried out based on the Doppler Effect, and then, the range imaging is performed by using compressive sensing of parallel frequencies signal. Several simulations demonstrate the feasibility and superiority of PFSAR via compressive sensing.