北京航空航天大学学报 ›› 2014, Vol. 40 ›› Issue (1): 59-62.

• 论文 • 上一篇    下一篇

压缩感知合成孔径雷达射频干扰抑制处理

麦超云1, 孙进平1, 崔如心1, 张冰尘2   

  1. 1. 北京航空航天大学 电子信息工程学院, 北京 100191;
    2. 中国科学院 微波成像技术国家重点实验室, 北京 100190
  • 收稿日期:2013-03-06 出版日期:2014-01-20 发布日期:2014-01-22
  • 基金资助:
    国家973计划资助项目(2010CB731903)

RFI suppression processing for compressive sensing based SAR imaging

Mai Chaoyun1, Sun Jinping1, Cui Ruxin1, Zhang Bingchen2   

  1. 1. School of Electronic and Information Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China;
    2. National Key Lab of MW Imaging Technology, Chinese Academy of Sciences, Beijing 100190, China
  • Received:2013-03-06 Online:2014-01-20 Published:2014-01-22

摘要: 对基于压缩感知技术的合成孔径雷达(SAR,Synthetic Aperture Radar)成像,射频干扰(RFI,Radio Frequency Interference)的存在会破坏场景稀疏的先验条件,造成成像质量恶化,使得后续的成像处理无法正确完成的问题,提出了一种压缩感知SAR的RFI抑制方法.首先基于RFI在频域的稀疏特征,采用贪婪算法结合最小描述长度(MDL,Minimum Description Length)估计出RFI分量稀疏度;然后对每个脉冲的回波信号,估计RFI信号分量并在时域直接滤除,再应用常规的压缩感知SAR重构算法实现成像处理.L波段SAR数据的仿真处理结果验证了文中方法的有效性.

Abstract: To the synthetic aperture radar (SAR) imaging system which uses compressive sensing (CS) technology, radio frequency interference (RFI) would undermine the priori sparse condition and cause deterioration of image quality, making the subsequent reconstruction algorithm complete the imaging process incorrectly. A RFI suppression method of CS SAR was proposed. The greedy algorithm combined with minimum description length (MDL) criteria was used to estimate the RFI components sparsity, according to the RFI sparse characteristics in the frequency domain. For each pulse data, the RFI signal components were estimated and filtered in the time domain directly. Then conventional CS SAR reconstruction algorithm can be applied to achieve imaging output. The simulation results of L-band SAR data verify the effectiveness of this method.

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