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A Data processing technique of removing DC railway noise from time domain magnetotelluric data, 2

Makuuchi, Ayumu; Asamori, Koichi; Negi, Tateyuki*

Even though applying the far remote reference magnetotelluric (MT) method, we need long recording period to obtain usable data from the contaminated data by strong and coherent noise in DC railway area. In this study, we consider the electric time series model including a trend component, natural magnetic signal response, correlated noise components, and white noise, then attempt to separate to each component with a Kalman filter algorithm. The method was applied to the magnetotelluric data observed near the DC railway and seems to work well in the time domain.

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