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dc.contributor.authorHyuk, Park
dc.contributor.authorGonzalez Gambau, Verónica
dc.contributor.authorCamps Carmona, Adriano José
dc.contributor.authorVall-Llossera Ferran, Mercedes Magdalena
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
dc.identifier.citationPark, H., Gonzalez, V., Camps, A., Vall-llossera, M. Improved MUSIC-based SMOS RFI source detection and geolocation algorithm. "IEEE transactions on geoscience and remote sensing", 01 Març 2016, vol. 54, núm. 3, p. 1311-1322.
dc.description©2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.description.abstractThe European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission has been providing L-band brightness temperature (BT) using its instrument, the Microwave Imaging Radiometer using Aperture Synthesis. In the measurements, the negative effect of radio frequency interference (RFI) is clearly present, deteriorating the quality of geophysical parameter retrieval. Detection and geolocation of RFI sources are essential to remove or at least mitigate the RFI impacts and ultimately improve the performance of parameter retrieval. This paper discusses a new approach to SMOS RFI source detection, based on the MUltiple SIgnal Classification (MUSIC) algorithm. Recently, the feasibility of MUSIC direction-of-arrival estimation has been shown for the RFI source detection of the synthetic aperture interferometric radiometer. This paper refines the MUSIC RFI source detection algorithm and tailors it to the SMOS scenario. To consolidate the RFI source detection procedure, several required steps are devised, including the rank estimation of the covariance matrix, local peak detection and thresholds, andmultiple-snapshot processing. The developed method is tested using a number of SMOS visibility samples. In the test results, the MUSIC method shows an improvement on the accuracy and precision of the RFI source geolocation, compared with a simple detection method based on the local peaks of BT images. The MUSIC results especially outperform the SMOS BT image on the spatial resolution.
dc.format.extent12 p.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Circuits de microones, radiofreqüència i ones mil·limètriques
dc.subject.lcshSoil moisture--Measurement
dc.subject.lcshRadio frequency
dc.subject.otherDirection-of-arrival (DOA) estimation
dc.subject.otherMicrowave radiometry
dc.subject.otherRadio frequency interferences (RFIs)
dc.subject.otherSoil moisture and ocean salinity (SMOS) mission
dc.subject.otherSynthetic aperture radiometry
dc.subject.otherInterferometric radiometers
dc.titleImproved MUSIC-based SMOS RFI source detection and geolocation algorithm
dc.subject.lemacSòls -- Humitat -- Mesurament
dc.contributor.groupUniversitat Politècnica de Catalunya. CTE-CRAE - Grup de Recerca en Ciències i Tecnologies de l'Espai
dc.contributor.groupUniversitat Politècnica de Catalunya. RSLAB - Grup de Recerca en Teledetecció
dc.description.peerreviewedPeer Reviewed
dc.rights.accessOpen Access
dc.description.versionPostprint (author's final draft)
upcommons.citation.authorPark, H., Gonzalez, V., Camps, A., Vall-llossera, M.
upcommons.citation.publicationNameIEEE transactions on geoscience and remote sensing

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