Parallel frequency radar via compressive sensing

Traditional radar utilizes Shannon-Nyquist theorem for high bandwidth signal sampling, which induces the complicated system. Compressive sensing (CS) indicates that the compressible signal using a few measurements can be reconstructed by solving a convex optimization problem. Thus, the huge amount of data according to high Shannon Nyquist rate is significantly reduced by compressive sensing. Parallel frequency radar theoretically cannot degrade the resolution compared with a traditional radar system and effectively reduces the sampling rate. In this paper, we focus on the data processing of the novel radar system. Basing on a sufficient structure, an algorithm of target scene reconstruction in pursuance of compressive sensing applied to the novel radar is proposed. Several simulations demonstrate the feasibility and the superiority of parallel frequency radar via compressive sensing.