利用可变空频滤波器缓解合成孔径雷达中的窄带射频干扰

Nermine Hendy;Akram Al-Hourani;Thomas Kraus;Maximilian Schandri;Markus Bachmann;Haytham M. Fayek
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摘要

合成孔径雷达(SAR)中的射频干扰(RFI)是一项艰巨的挑战,会影响传感可靠性和图像质量。为确保合成孔径雷达继续成为地球观测的有力工具,本文提出了一种二维可变衰减空间(方位角)-频率滤波(VASFF)方法。该框架利用零级合成孔径雷达数据的时频特征、射频干扰功率曲线、估计的射频干扰信号参数和合成孔径雷达天线模式来设计新型可变滤波器。信号功率定位可估算干扰源的相对位置,从而方便滤波器的应用。使用我们的开源仿真器 SEMUS 生成干净和受干扰污染的原始合成孔径雷达数据所获得的仿真结果表明,所提出的滤波器比传统的陷波滤波器提高了 2 dB。该框架在 TerraSAR-X 的真实干扰事件中进行了进一步测试,揭示了之前被遮挡的图像细节,验证了该框架的有效性。
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Narrow-Band RFI Mitigation in Synthetic Aperture Radars Using Variable Space-Frequency Filter
Radio frequency interference (RFI) in synthetic aperture radar (SAR) is a daunting challenge, affecting both sensing reliability and image quality. To ensure that SAR remains a powerful tool for Earth observation, this letter presents a 2-D variable attenuation space (azimuth)-frequency filtration (VASFF) method. This framework leverages the time-frequency characteristics of Level-0 SAR data, the RFI power profile, estimated RFI signal parameters, and the SAR antenna pattern to design a novel variable filter. Signal power localization estimates the interference source’s relative position, facilitating filter application. Simulated results, obtained using our open-source emulator, SEMUS, to generate both clean and interference-contaminated raw SAR data, demonstrate that the proposed filter achieves a 2 dB improvement over traditional notch filtering. The framework is further tested on real-life interference events on TerraSAR-X revealing previously obscured image details, validating the framework’s effectiveness.
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