A Novel Algorithm for Synthetic Aperture Radar Imaging Based on Compressed Sensing
To achieve high-resolution images, synthetic aperture radar (SAR) faces considerable technical challenges such as huge amount of data samples and high hardware complexity. Compressed sensing (CS) theory shows that the super-resolved images can be reconstructed from an extremely smaller set of measurements than what is generally considered necessary by Nyquist/Shannon theorem. In this paper, a new algorithm of SAR imaging based on the concept of CS is presented, in which a random fractional Fourier transform (FRFT) matrix is used as the sensing matrix. By utilizing the FRFT matrix the demodulator for de-ramping the linear frequency modulation signal can be eliminated. Simulation results with both simulated and real data exhibit the validity of the proposed algorithm.
Compressed Sensing Synthetic Aperture Radar Fractional Fourier Transform
Hongxia Bu Xia Bai Ran Tao
Department of Electronic Engineering, Beijing Institute of Technology, Beijing, China
国际会议
2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)
北京
英文
2210-2213
2010-08-24（万方平台首次上网日期，不代表论文的发表时间）