MIRAS end-to-end calibration: application to SMOS L1 processor

End-to-end calibration of the Microwave Imaging Radiometer by Aperture Synthesis (MIRAS) radiometer refers to processing the measured raw data up to dual-polarization brightness temperature maps over the earth's surface, which is the level 1 product of the Soil Moisture and Ocean Salinity (SMOS...

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Detalles Bibliográficos
Autores: Vall-Llossera Ferran, Mercedes Magdalena|||0000-0003-1357-7098, Corbella Sanahuja, Ignasi|||0000-0001-5598-7955, Torres Torres, Francisco|||0000-0003-1160-6350, Camps Carmona, Adriano José|||0000-0002-9514-4992, Colliander, A, Martín Neira, Manuel, Ribó Vedrilla, Serni|||0000-0002-9173-8355, Rautiainen, K, Duffo Ubeda, Núria|||0000-0002-9398-3995
Tipo de recurso: artículo
Fecha de publicación:2005
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/10105
Acceso en línea:https://hdl.handle.net/2117/10105
https://dx.doi.org/10.1109/TGRS.2004.840458
Access Level:acceso abierto
Palabra clave:Microwave measurements
Remote sensing
Image reconstruction
Microones -- Mesurament
Radiòmetres -- Calibració
Sensors remots
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Circuits de microones, radiofreqüència i ones mil·limètriques
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica
Descripción
Sumario:End-to-end calibration of the Microwave Imaging Radiometer by Aperture Synthesis (MIRAS) radiometer refers to processing the measured raw data up to dual-polarization brightness temperature maps over the earth's surface, which is the level 1 product of the Soil Moisture and Ocean Salinity (SMOS) mission. The process starts with a self-correction of comparators offset and quadrature error and is followed by the calibration procedure itself. This one is based on periodically injecting correlated and uncorrelated noise to all receivers in order to measure their relevant parameters, which are then used to correct the raw data. This can deal with most of the errors associated with the receivers but does not correct for antenna errors, which must be included in the image reconstruction algorithm. Relative S-parameters of the noise injection network and of the input switch are needed as additional data, whereas the whole process is independent of the exact value of the noise source power and of the distribution network physical temperature. On the other hand, the approach relies on having at least one very well-calibrated reference receiver, which is implemented as a noise injection radiometer. The result is the calibrated visibility function, which is inverted by the image reconstruction algorithm to get the brightness temperature as a function of the director cosines at the antenna reference plane. The final step is a coordinate rotation to obtain the horizontal and vertical brightness temperature maps over the earth. The procedures presented are validated using a complete SMOS simulator previously developed by the authors.