Signal discrimination of ULF electromagnetic data with using singular spectrum analysis – an attempt to detect train noise
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 di...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2011-07-01
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| Series: | Natural Hazards and Earth System Sciences |
| Online Access: | http://www.nat-hazards-earth-syst-sci.net/11/1863/2011/nhess-11-1863-2011.pdf |
| Summary: | 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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| ISSN: | 1561-8633 1684-9981 |