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| Titel |
Signal discrimination of ULF electromagnetic data with using singular spectrum analysis – an attempt to detect train noise |
| VerfasserIn |
S. Saito, D. Kaida, K. Hattori, F. Febriani, C. Yoshino |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1561-8633
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| Digitales Dokument |
URL |
| Erschienen |
In: Natural Hazards and Earth System Science ; 11, no. 7 ; Nr. 11, no. 7 (2011-07-07), S.1863-1874 |
| Datensatznummer |
250009557
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| Publikation (Nr.) |
 copernicus.org/nhess-11-1863-2011.pdf |
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| Zusammenfassung |
| Electromagnetic phenomena associated with crustal activities have been
reported in a wide frequency range (DC-HF). In particular, ULF
electromagnetic phenomena are the most promising among them because of the
deeper skin depth. However, ULF geoelctromagnetic data are a superposition of
signals of different origins. They originated from interactions between
the geomagnetic field and the solar wind, leak current by a DC-driven train
(train noise), precipitation, and so on. In general, the intensity of
electromagnetic signals associated with crustal activity is smaller than
the above variations. Therefore, in order to detect a smaller signal, signal
discrimination such as noise reduction or identification of noises is very
important. In this paper, the singular spectrum analysis (SSA) has been
performed to detect the DC-driven train noise in geoelectric potential
difference data. The aim of this paper is to develop an effective algorithm
for the DC-driven train noise detection. |
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