On the potential of empirical mode decomposition for RFI mitigation in microwave radiometry

Radio-frequency interference (RFI) is an increasing problem particularly for Earth observation using microwave radiometry. RFI has been observed, for example, at L-band by the European Space Agency’s (ESA’s) soil moisture and ocean salinity (SMOS) Earth Explorer and by National Aeronautics and Space...

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Detalles Bibliográficos
Autores: Díez García, Raúl, Camps Carmona, Adriano José|||0000-0002-9514-4992, Hyuk, Park|||0000-0003-0031-0802
Tipo de recurso: artículo
Fecha de publicación:2022
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:2117/374526
Acceso en línea:https://hdl.handle.net/2117/374526
https://dx.doi.org/10.1109/TGRS.2022.3188171
Access Level:acceso abierto
Palabra clave:Microwave remote sensing
Imaging systems in geophysics
Hilbert–Huang transform (HHT)
Interference
Microwave radiometer
Passive microwave remote sensing
Radiofrequency interference (RFI)
RFI detection
Teledetecció per microones
Imatgeria en geofísica
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Teledetecció
Descripción
Sumario:Radio-frequency interference (RFI) is an increasing problem particularly for Earth observation using microwave radiometry. RFI has been observed, for example, at L-band by the European Space Agency’s (ESA’s) soil moisture and ocean salinity (SMOS) Earth Explorer and by National Aeronautics and Space Administration’s (NASA’s) soil moisture active passive (SMAP) and Aquarius missions, as well as at C-band by Advanced Microwave Scanning Radiometer (AMSR)-E and AMSR-2, and at 10.7 and 18.7 GHz by AMSR-E, AMSR-2, WindSat, and GPM Microwave Imager (GMI). Therefore, systems dedicated to interference detection and removal of contaminated measurements are nowadays a must in order to improve radiometric accuracy and reduce the loss of spatial coverage caused by interference. In this work, the feasibility of using the empirical mode decomposition (EMD) technique for RFI mitigation is explored. The EMD, also known as Hilbert–Huang transform (HHT), is an algorithm that decomposes the signal into intrinsic mode functions (IMFs). The achieved performance is analyzed, and the opportunities and caveats that this type of methods present are described. EMD is found to be a practical RFI mitigation method, albeit presenting some limitations and considerable complexity. Nevertheless, in some conditions, EMD exhibits a better performance than other commonly used methods (such as frequency binning). In particular, it has been found that EMD performs well for RFI affecting the <25% lower part of the intermediate frequency (IF) bandwidth.