Automatic $P$-Phase Picking Based on Local-Maxima Distribution

In this paper, we propose a method for the automatic identification of P-phase arrival based on the distribution of local maxima (LM) in earthquake seismograms. The method efficiently combines energy and frequency characteristics of the LM distribution (LMD). The detection is mainly based on the energy of a seismic event in the case the earthquake has higher amplitude than seismic background noise. Otherwise, it is based on the frequency of LM. Thus, the method provides robust detection of P-phase arrival in any quality type of seismic data. Moreover, it uses two sequential sliding signal windows yielding very high accuracy on the P-phase estimation. A hierarchical P-phase detection algorithm dramatically reduces the computational cost, making possible a real-time implementation. Experimental results from a large database of more than 80 low, medium, and high signal-to-noise ratio seismic events and comparison with existing methods in the literature indicate the reliable performance of the proposed scheme.