Remote Sensing Applications and Decision Support

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

[+] Author Affiliations
Hailiang Lu, Qingxia Li, Yan Li

Huazhong University of Science and Technology, School of Electronic Information and Communications, 1037 Luoyu Road, Wuhan 430074, China

Yinan Li, Hao Li

Xi’an Institute of Space Radio Technology, 504 Chang'an Eastern Street, Xi’an 710100, China

J. Appl. Remote Sens. 9(1), 095996 (Oct 14, 2015). doi:10.1117/1.JRS.9.095996
History: Received May 27, 2015; Accepted September 9, 2015
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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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© 2015 Society of Photo-Optical Instrumentation Engineers

Citation

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", J. Appl. Remote Sens. 9(1), 095996 (Oct 14, 2015). ; http://dx.doi.org/10.1117/1.JRS.9.095996


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