Clustering of EM radiation source based on eigenvector

Our goal is to locate anomalous electromagnetic (EM) sources caused by seismic activity for earthquake prediction. For the purpose, we have measured the EM wave of 223Hz at 35 sites in Japan. The measured signal contains much noise caused by lightning around the equator, human activity, near field lightning and so on. EM noises from far sources can be eliminated by using correlation in multi-point observation. But near-field noise is not easy to eliminate. This paper shows that the principal component analysis methods for covariance matrices of measured signals are effective for clustering signals and separating each source. It is shown that a result to estimate thunder lightning location in near field agrees with real thundercloud observed by radar system. And results of estimation of sources of anomalous EM radiation occurred before and after earthquake are also shown.