Precursor signal estimation using ELF band observations for predicting earthquakes using Monte Carlo filter

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 of the background noise in the captured signals is attributed to lightning in the tropics. In this paper, we introduce a self-tuned state space model and a Monte Carlo filter to reduce the noise. The good performance of the proposed method is confirmed.