Low-level radio-frequency interference detection algorithm based on European Centre for Medium-Range Weather Forecasting for Soil Moisture and Ocean Salinity

Hailiang Lu; Qingxia Li; Yan Li; Yinan Li; Hao Li

doi:10.1117/1.JRS.9.095996

14 October 2015 Low-level radio-frequency interference detection algorithm based on European Centre for Medium-Range Weather Forecasting for Soil Moisture and Ocean Salinity

Hailiang Lu, Qingxia Li, Yan Li, Yinan Li, Hao Li

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 9, Issue 1, 095996 (October 2015). https://doi.org/10.1117/1.JRS.9.095996

Abstract

At present, the Soil Moisture and Ocean Salinity (SMOS) mission is severely affected by radio frequency interferences (RFIs), and the detection of low-level RFI-contamination brightness temperatures (BTs) is still a challenge in SMOS. A low-level RFI detection algorithm is proposed, which is based on the soil surface temperature products provided by the European Centre for Medium-Range Weather Forecasting. The algorithm is analyzed in terms of RFI-flagged snapshot, RFI-flagged probability, and localization accuracy. The performance of the algorithm is demonstrated by SMOS data. The results show this algorithm can detect and flag more low-level RFI-contamination BTs and show a better performance.

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Hailiang Lu, Qingxia Li, Yan Li, Yinan Li, and Hao Li "Low-level radio-frequency interference detection algorithm based on European Centre for Medium-Range Weather Forecasting for Soil Moisture and Ocean Salinity," Journal of Applied Remote Sensing 9(1), 095996 (14 October 2015). https://doi.org/10.1117/1.JRS.9.095996

Published: 14 October 2015

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