Abstract
By using multiple reference stations, we have developed a method to get reliable ULF global geomagnetic variations. This background is extremely useful for detecting local anomalous behaviors. This paper demonstrates developed variable tools to identify the anomalies in two frequency ranges; daily variation and 10-1000 seconds. For estimating background daily variations, the periodical model has been applied for data observed at 3 reference stations and a study station. Comparison between the first principal component of the periodical data from the reference stations and the periodical data derived from the target station provides high correlation in general. For data with 100 sec periods after wavelet filtering, the nighttime energy variations have been investigated among 3 reference stations and a study station. The similar principal component analysis as the diurnal variation has been performed and results also show high correlation between the variation at the target and the global background. These tendency suggest that the developed two methods are effective to identify the anomalies in automatic. Examining the original data, we can know details of waveform and distinguish whether the anomalies is related to underground activities or just some artificial noises.
