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压缩感知合成孔径雷达射频干扰抑制处理 被引量:2

RFI suppression processing for compressive sensing based SAR imaging
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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. 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 deteri oration of image quality, making the subsequent reconstruction algorithm complete the imaging process incor rectly. A RFI suppression method of CS SAR was proposed. The greedy algorithm combined with minimum de scription 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 a chieve imaging output. The simulation results of Lband SAR data verify the effectiveness of this method.
出处 《北京航空航天大学学报》 EI CAS CSCD 北大核心 2014年第1期59-62,共4页 Journal of Beijing University of Aeronautics and Astronautics
基金 国家973计划资助项目(2010CB731903)
关键词 合成孔径雷达 射频干扰抑制 压缩感知 贪婪算法 最小描述长度 synthetic aperture radar (SAR) radio frequency interference (RFI) suppression compres-sive sensing(CS) greedy algorithm minimum description length(MDL)
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参考文献12

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