The Signal Detection for Predicting Significant Earthquake Using PCA

Abstract

The tectonic activities that precede significant earthquakes release electromagnetic (EM) waves that can be used as earthquake precursors. We have been observing EM radiation in the ELF (extremely low frequency) band at about 40 observation stations in Japan for predicting significant earthquakes. The recorded signals contain, however, several noise components generated from the ionosphere, human activity, and so on. Most background noise in observed signal is attributed to lightning in the tropics. In this paper, we propose a method based on PCA (principal component analysis) to detect signals from large data sets. The good performance of the proposed method is confirmed.