IEEE Transactions on Geoscience and Remote Sensing, volume 52, issue 11, pages 7038-7047
A Kurtosis-Based Approach to Detect RFI in SMOS Image Reconstruction Data Processor
1
Center for the Study of the BIOsphere (CESBIO), Universitè de Toulouse, CNRS, CNES & IRD, Toulouse, France
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2
Research Institute of Astrophysics and Planetology, Observatoire Midi-Pyrénées, Toulouse, France
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Publication type: Journal Article
Publication date: 2014-11-01
Q1
Q1
SJR: 2.403
CiteScore: 11.5
Impact factor: 7.5
ISSN: 01962892, 15580644
Electrical and Electronic Engineering
General Earth and Planetary Sciences
Abstract
The Soil Moisture and Ocean Salinity (SMOS) mission is a European Space Agency project aimed to observe two important geophysical variables, i.e., soil moisture over land and ocean salinity by L-band microwave imaging radiometry. This work is concerned with the contamination of the SMOS data by radio-frequency interferences (RFIs), which degrades the performance of the mission. In this paper, we propose an approach that detects if a given snapshot is contaminated, or not, by RFI. This approach is based on evaluating the kurtosis of each snapshot or data set, using all interferometric measurements provided by the instrument. The obtained kurtosis is considered as an indicator on how much the snapshot is polluted by RFI, thus allowing the user to decide on whether to keep or discard it.
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Khazaal A. et al. A Kurtosis-Based Approach to Detect RFI in SMOS Image Reconstruction Data Processor // IEEE Transactions on Geoscience and Remote Sensing. 2014. Vol. 52. No. 11. pp. 7038-7047.
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Khazaal A., Cabot F., Anterrieu E., Soldo Y. A Kurtosis-Based Approach to Detect RFI in SMOS Image Reconstruction Data Processor // IEEE Transactions on Geoscience and Remote Sensing. 2014. Vol. 52. No. 11. pp. 7038-7047.
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TY - JOUR
DO - 10.1109/tgrs.2014.2306713
UR - https://doi.org/10.1109/tgrs.2014.2306713
TI - A Kurtosis-Based Approach to Detect RFI in SMOS Image Reconstruction Data Processor
T2 - IEEE Transactions on Geoscience and Remote Sensing
AU - Khazaal, Ali
AU - Cabot, François
AU - Anterrieu, Eric
AU - Soldo, Yan
PY - 2014
DA - 2014/11/01
PB - Institute of Electrical and Electronics Engineers (IEEE)
SP - 7038-7047
IS - 11
VL - 52
SN - 0196-2892
SN - 1558-0644
ER -
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@article{2014_Khazaal,
author = {Ali Khazaal and François Cabot and Eric Anterrieu and Yan Soldo},
title = {A Kurtosis-Based Approach to Detect RFI in SMOS Image Reconstruction Data Processor},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
year = {2014},
volume = {52},
publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
month = {nov},
url = {https://doi.org/10.1109/tgrs.2014.2306713},
number = {11},
pages = {7038--7047},
doi = {10.1109/tgrs.2014.2306713}
}
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MLA
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Khazaal, Ali, et al. “A Kurtosis-Based Approach to Detect RFI in SMOS Image Reconstruction Data Processor.” IEEE Transactions on Geoscience and Remote Sensing, vol. 52, no. 11, Nov. 2014, pp. 7038-7047. https://doi.org/10.1109/tgrs.2014.2306713.