DocumentCode :
2102391
Title :
GNSS Signal Interference Classified by Means of a Supervised Learning Method Applied in the Time-Frequency Domain
Author :
Cardellach, Estel ; Oliveras, Santiago ; Rius, Antonio
Author_Institution :
ICE-CSIC/IEEC, Inst. de Cienc. de I´´Espai, Barcelona, Spain
fYear :
2009
fDate :
17-19 Oct. 2009
Firstpage :
1
Lastpage :
5
Abstract :
Global Navigation Satellite System (GNSS) signals received by an occulting Low Earth Orbiter (LEO) often reflect on the Earth´s surface, thus interfering with the direct ray. For certain remote sensing applications, the identification and classification of the reflection events is required. We have taken advantage of the fact that interference patterns in the time-domain (oscillation of both received amplitude and phase) yield a clear feature in the frequency-time domain, to apply pattern recognition techniques onto the radioholographic images of the received electromagnetic field.
Keywords :
Earth orbit; geophysical signal processing; image classification; learning (artificial intelligence); radiofrequency interference; remote sensing; satellite navigation; time-frequency analysis; Earth surface; GNSS signal interference classification; Global Navigation Satellite System; electromagnetic field; low Earth orbiter; pattern recognition; radioholographic image recognition; remote sensing application; satellite radio-occultation observation; supervised learning method; time-frequency domain; Electromagnetic interference; Electromagnetic reflection; Global Positioning System; Low earth orbit satellites; Radiofrequency identification; Radiofrequency interference; Remote sensing; Satellite navigation systems; Supervised learning; Time frequency analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Signal Processing, 2009. CISP '09. 2nd International Congress on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4244-4129-7
Electronic_ISBN :
978-1-4244-4131-0
Type :
conf
DOI :
10.1109/CISP.2009.5302135
Filename :
5302135
Link To Document :
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