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Journal of Applied Remote Sensing

Low-level radio-frequency interference detection algorithm based on European Centre for Medium-Range Weather Forecasting for Soil Moisture and Ocean Salinity
Author(s): Hailiang Lu; Qingxia Li; Yan Li; Yinan Li; Hao Li
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Paper 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.

Paper Details

Date Published: 14 October 2015
PDF: 15 pages
J. Appl. Remote Sens. 9(1) 095996 doi: 10.1117/1.JRS.9.095996
Published in: Journal of Applied Remote Sensing Volume 9, Issue 1
Show Author Affiliations
Hailiang Lu, Huazhong Univ. of Science and Technology (China)
Qingxia Li, Huazhong Univ. of Science and Technology (China)
Yan Li, Huazhong Univ. of Science and Technology (China)
Yinan Li, Xi'an Institute of Space Radio Technology (China)
Hao Li, Xi’an Institute of Space Radio Technology (China)


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