Time-frequency tools of signal processing for EISCAT data analysis

International audience We demonstrate the usefulness of some signal-processing tools for the EISCAT data analysis. These tools are somewhat less classical than the familiar periodogram, squared modulus of the Fourier transform, and therefore not as commonly used in our community. The first is a stat...

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Bibliographic Details
Main Authors: Lilensten, J., Amblard, Pierre-Olivier
Other Authors: Centre d'Études des Phénomènes Aléatoires et Géophysiques (CEPHAG), École Nationale Supérieure d'Ingénieurs Électriciens de Grenoble (ENSIEG)-Centre National de la Recherche Scientifique (CNRS)
Format: Article in Journal/Newspaper
Language:English
Published: HAL CCSD 1996
Subjects:
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean
Atmosphere
[SDU.STU]Sciences of the Universe [physics]/Earth Sciences
EISCAT
Online Access:https://hal.science/hal-00329066
https://hal.science/hal-00329066/document
https://hal.science/hal-00329066/file/angeo-14-1513-1996.pdf
Description
Summary:International audience We demonstrate the usefulness of some signal-processing tools for the EISCAT data analysis. These tools are somewhat less classical than the familiar periodogram, squared modulus of the Fourier transform, and therefore not as commonly used in our community. The first is a stationary analysis, "Thomson's estimate'' of the power spectrum. The other two belong to time-frequency analysis: the short-time Fourier transform with the spectrogram, and the wavelet analysis via the scalogram. Because of the highly non-stationary character of our geophysical signals, the latter two tools are better suited for this analysis. Their results are compared with both a synthetic signal and EISCAT ion-velocity measurements. We show that they help to discriminate patterns such as gravity waves from noise.

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