An Imaging Algorithm for Random Noise Synthetic Aperture Radar Based on Double Spectral Signal Processing

摘要

Investigated here is an approach to random noise synthetic aperture radar (SAR) imaging. Combining random noise radar with SAR imaging, random noise SAR holds both advantages of the two individuals. Depending on delay units, conventional noise SAR imaging applies correlation to accomplish range compression. The range resolution is restricted by the step of delay unit. To avoid using delay units and correlation in receiver, double spectral processing is introduced to perform range pulse compression as an alternative option to direct correlation. Based on this signal processing method, a novel imaging algorithm for random noise SAR is proposed combining with traditional range-Doppler (RD) algorithm. The range compression is operated by one addition and three FFT (IFFT). The concepts of zero maximum envelope and focused plane are proposed. Theoretical derivation for this algorithm is presented. Simulation results demonstrate that the proposal algorithm is capable of getting high-quality images for random noise SAR system. Furthermore, the delay units and correlation in receiver is avoided completely, and the requirement of real time processing is reduced.