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首页> 外文期刊>Geoscience and Remote Sensing, IEEE Transactions on >A First Set of Techniques to Detect Radio Frequency Interferences and Mitigate Their Impact on SMOS Data
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A First Set of Techniques to Detect Radio Frequency Interferences and Mitigate Their Impact on SMOS Data

机译：第一套检测射频干扰并减轻其对SMOS数据影响的技术

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摘要

The presence of radio frequency interferences (RFIs) in the data collected by the Soil Moisture and Ocean Salinity (SMOS) mission led by the European Space Agency is larger than what was anticipated, and it has a strong impact on the retrieval of these geophysical parameters. The first efforts to deal with this problem were proposed by DEIMOS Engenharia in the Level 1 Prototype Processor released in November 2010, and they are also a part of its latest versions. DEIMOS focused on three key aspects to detect the RFIs, to mitigate these sources, and to flag the data in SMOS products affected by RFIs. The detection algorithm is based on a statistic approach that computes the most probable position of the RFI source based on multiangular observations made by SMOS. The mitigation algorithm has been designed taking as reference the existing technique to remove the sun effect. The mechanism to flag the data has been developed in cooperation with the European Space Agency and consists in flagging geolocated pixels according to the strength of the RFI. In this paper, three algorithms will be presented, as well as their results. For completion, a high-level description of the data processing for SMOS is also a part of this text.
机译：由欧洲航天局领导的土壤水分和海洋盐度（SMOS）任务收集的数据中存在射频干扰（RFI），其数量比预期的要大，并且对这些地球物理参数的检索有很大影响。 DEIMOS Engenharia在2010年11月发布的1级原型处理器中提出了解决该问题的第一项努力，它们也是其最新版本的一部分。 DEIMOS专注于检测RFI，减轻这些来源以及标记受RFI影响的SMOS产品中的数据的三个关键方面。该检测算法基于一种统计方法，该方法基于SMOS进行的多角度观测来计算RFI源的最可能位置。在设计缓解算法时，已参考现有的消除日光效应的技术。与欧洲航天局合作开发了标记数据的机制，该机制包括根据RFI的强度标记地理像素。在本文中，将介绍三种算法及其结果。为了完整起见，本文还将对SMOS的数据处理进行高级描述。

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