SMOS L1 algorithms

Gutierrez, Antonio P.; Barbosa, José; Catarino, Nuno; Castro, Rita; Freitas, Sandra C.; Lucas, Bruno; Candeias, Henrique; Freitas, Jose Cabrita A.; Ventura, M. A.; Zundo, Michele

doi:10.1109/igarss.2010.5650097

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Calibration Of Parameters Needed In1

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“…In addition, operational calibration issues and calibration timeline of SMOS is discussed in detail e.g. in [132], and [133]. The calibration strategies implemented for the HUT-2D instrument are reviewed in more detail in Section 4.5.1.…”

Section: Calibration Of Parameters Needed Inmentioning

confidence: 99%

Detection of a Sea Surface Salinity Gradient Using Data Sets of Airborne Synthetic Aperture Radiometer HUT-2-D and a GNSS-R Instrument

Kainulainen

Rautiainen

Lemmetyinen

et al. 2011

IEEE Trans. Geosci. Remote Sensing

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Section: Calibration Of Parameters Needed Inmentioning

confidence: 99%

Detection of a Sea Surface Salinity Gradient Using Data Sets of Airborne Synthetic Aperture Radiometer HUT-2-D and a GNSS-R Instrument

Kainulainen

Rautiainen

Lemmetyinen

et al. 2011

IEEE Trans. Geosci. Remote Sensing

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A First Set of Techniques to Detect Radio Frequency Interferences and Mitigate Their Impact on SMOS Data

Castro

Gutierrez

Barbosa

2012

IEEE Trans. Geosci. Remote Sensing

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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.

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SMOS L1 algorithms

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Cited by 2 publications

References 1 publication

Detection of a Sea Surface Salinity Gradient Using Data Sets of Airborne Synthetic Aperture Radiometer HUT-2-D and a GNSS-R Instrument

Detection of a Sea Surface Salinity Gradient Using Data Sets of Airborne Synthetic Aperture Radiometer HUT-2-D and a GNSS-R Instrument

A First Set of Techniques to Detect Radio Frequency Interferences and Mitigate Their Impact on SMOS Data

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