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Improved MUSIC-Based SMOS RFI Source Detection and Geolocation Algorithm

机译:基于MUSIC的改进SMOS RFI源检测和地理位置算法

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摘要

The European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission has been providing L-band brightness temperature (BT) using its instrument, the Microwave Imaging Radiometer using Aperture Synthesis. In the measurements, the negative effect of radio frequency interference (RFI) is clearly present, deteriorating the quality of geophysical parameter retrieval. Detection and geolocation of RFI sources are essential to remove or at least mitigate the RFI impacts and ultimately improve the performance of parameter retrieval. This paper discusses a new approach to SMOS RFI source detection, based on the MUltiple SIgnal Classification (MUSIC) algorithm. Recently, the feasibility of MUSIC direction-of-arrival estimation has been shown for the RFI source detection of the synthetic aperture interferometric radiometer. This paper refines the MUSIC RFI source detection algorithm and tailors it to the SMOS scenario. To consolidate the RFI source detection procedure, several required steps are devised, including the rank estimation of the covariance matrix, local peak detection and thresholds, and multiple-snapshot processing. The developed method is tested using a number of SMOS visibility samples. In the test results, the MUSIC method shows an improvement on the accuracy and precision of the RFI source geolocation, compared with a simple detection method based on the local peaks of BT images. The MUSIC results especially outperform the SMOS BT image on the spatial resolution.
机译:欧洲航天局的土壤湿度和海洋盐度(SMOS)任务一直在使用其仪器,使用光圈合成的微波成像辐射仪提供L波段亮度温度(BT)。在测量中,很明显存在射频干扰(RFI)的负面影响,从而降低了地球物理参数检索的质量。 RFI源的检测和地理定位对于消除或至少减轻RFI影响并最终改善参数检索的性能至关重要。本文讨论了一种基于多信号分类(MUSIC)算法的SMOS RFI源检测新方法。最近,已经证明了MUSIC到达方向估计在合成孔径干涉辐射计的RFI源检测中的可行性。本文完善了MUSIC RFI源检测算法,并将其调整为SMOS方案。为了整合RFI源检测程序,设计了几个必需的步骤,包括协方差矩阵的秩估计,局部峰值检测和阈值以及多次快照处理。使用许多SMOS可见性样本测试了开发的方法。在测试结果中,与基于BT图像局部峰值的简单检测方法相比,MUSIC方法显示了RFI源地理定位的准确性和精确性。 MUSIC结果在空间分辨率上尤其胜过SMOS BT图像。

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