Estimation of geomagnetic field disturbance using the wavelet transform

This paper discusses the main aspects of geomagnetic data processing using the wavelet transform. The wavelet transform is shown to be efficient for automatic extraction of unperturbed level of the horizontal component of the Earth’s magnetic field. As a result, it becomes possible to significantly...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Pattern recognition and image analysis Ročník 26; číslo 4; s. 773 - 781
Hlavní autori: Mandrikova, O. V., Solovjev, I. S., Khomutov, S. Yu, Baishev, D. G., Geppener, V. V., Klionskiy, D. M.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Moscow Pleiades Publishing 01.10.2016
Springer Nature B.V
Predmet:
Analysis
Applied Problems
Automation
Computer Science
Data processing
Disturbances
Geomagnetic fields
Geomagnetism
Image Processing and Computer Vision
Magnetic fields
Magnetism
Mathematical analysis
Observatories
Pattern Recognition
Propagation
Smoothing
Storms
Studies
Wavelet transforms
geomagnetic activity index
geomagnetic data processing
Earth’s magnetic field
magnetic storm
wavelet transform
ISSN:1054-6618, 1555-6212
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:This paper discusses the main aspects of geomagnetic data processing using the wavelet transform. The wavelet transform is shown to be efficient for automatic extraction of unperturbed level of the horizontal component of the Earth’s magnetic field. As a result, it becomes possible to significantly reduce the errors arising during automatic calculations of the local geomagnetic activity index (local K-index) in comparison with adaptive smoothing (KAsm is Adaptative Smoothing method) recommended by INTERMAGNET. It has been found that prior to magnetic storms, we can observe a weak rise of geomagnetic activity in different frequency bands connected with the development of an approaching storm.
Bibliografia:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ObjectType-Article-1
ObjectType-Feature-2
content type line 23
ISSN:1054-6618
1555-6212
DOI:10.1134/S1054661816040076