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RFI Source Localization in Microwave Interferometric Radiometry: A Sparse Signal Reconstruction Perspective

机译:微波干涉辐射测定中的RFI源定位:稀疏信号重建透视图

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The Microwave Interferometric Radiometer with Aperture Synthesis (MIRAS) is the payload of the Soil Moisture and Ocean Salinity (SMOS) satellite mission led by the European Space Agency. Although the MIRAS operates at the protected L-band, it is perturbed by radio frequency interferences (RFIs) that contaminate the acquired remote sensing data and further deteriorate the total performance of SMOS mission. Accurate location information of these sources is crucial for switching off illegal RFI emitters or mitigating RFI impacts from contaminated data. This article addresses the localization of SMOS RFI sources from a perspective of sparse signal reconstruction (SSR), which exploits the sparsity of RFI sources in the spatial domain. Such an SSR strategy possesses superior (at least comparable) performances over existing RFI localization methods [e.g., discrete Fourier transformation (DFT) inversion and subspace-based direction-of-arrival (DOA) estimation] using only SMOS measurements and even under situations in the presence of data missing due to correlator failures.
机译:微波干涉测量辐射计具有孔径合成(MIRAS)是由欧洲航天局领导的土壤水分和海洋盐度(SMOS)卫星任务的有效载荷。虽然Miras在受保护的L波段运行,但它被污染所获取的遥感数据污染的射频干扰(RFI)扰乱,并且进一步恶化了SMOS任务的总性能。这些来源的准确位置信息对于关闭非法RFI发射器或减轻来自受污染数据的影响力是至关重要的。本文通过稀疏信号重建(SSR)的角度来解决SMOS RFI源的定位,该稀疏信号重建(SSR)利用空间域中RFI源的稀疏性。这种SSR策略具有优于现有RFI定位方法的优越(至少可比较)性能[例如,离散傅里叶变换(DFT)反转和基于子空间的到达方式(DOA)估计)仅使用SMOS测量,甚至在情况下由于相关器故障,存在数据缺失的存在。

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