Articles | Volume 11, issue 7
https://doi.org/10.5194/nhess-11-1863-2011
https://doi.org/10.5194/nhess-11-1863-2011
Research article
 | 
07 Jul 2011
Research article |  | 07 Jul 2011

Signal discrimination of ULF electromagnetic data with using singular spectrum analysis – an attempt to detect train noise

S. Saito, D. Kaida, K. Hattori, F. Febriani, and C. Yoshino

Abstract. 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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