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Abstract. To investigate high frequency geoacoustic emission, a receiving system based on a compound vector receiver was installed in Kamchatka. It allows the authors to determine the direction of sound wave arrival. In the result of data analysis for the period from August 2008 to January 2016, it was determined that anomalies of geoacoustic emission directivity occur during the majority of the earthquakes with K s > 9.0 in the South of Kamchatka.

Studies of geoacoustic emission in a seismically active region in Kamchatka show that geoacoustic signals produce pronounced pulse anomalies during the earthquake preparation and post-seismic relaxation of the local stresses field at the observation point. The qualitative selection of such anomalies is complicated by a strong distortion and weakening of the signal amplitude. A review of existing acoustic emission analysis methods shows that most often researchers turn to the analysis of more accessible to study statistical properties and energy of signals. The distinctive features of the approach proposed by the authors are the extraction of informative features based on the analysis of time and frequency-time structures of geoacoustic signals and the description of various forms of recognizable pulses by a limited pattern set. This study opens up new ideas to develop methods for detecting anomalous behavior of geoacoustic signals, including anomalies before earthquakes. The paper describes a technique of information extraction from geoacoustic emission pulse streams of sound frequency range. A geoacoustic pulse mathematical model, reflecting the signal generation process from a variety of elementary sources, is presented. A solution to the problem of detection of geoacoustic signal informative features is presented by the means of description of signal fragments by the matrixes of local extrema amplitude ratios and of interval ratios between them. The result of applying the developed algorithm to describe automatically the structure of the detected pulses and to form a pattern set is shown. The patterns characterize the features of geoacoustic emission signals observed at IKIR FEB RAS field stations. A technique of reduction of the detected pulse set dimensions is presented. It allows us to find patterns similar in structure. A solution to the problem of processing of a large data flow by unifying pulses description and their systematization is proposed. A method to identify a geoacoustic emission pulse model using sparse approximation schemes is suggested. An algorithmic solution of the problem of reducing the computational complexity of the matching pursuit method is described. It is to include an iterative refinement algorithm for the solution at each step in the method. The results of the research allowed the authors to create a tool to investigate the dynamic properties of geoacoustic emission signal in order to develop earthquake prediction detectors.

The article describes the results of complex analysis of pre-seismic signals of electromagnetic and geoacoustic radiation. We analyzed the frequency content of single sferics and geoacoustic impulses recorded before the Zhupanov earthquake that occurred on January 30, 2016. The signals were analyzed using sparse approximation method, in particular Adaptive Matched Pursuit. Background signals were studied together with pre-seismic ones. Distributions of frequencies, that are part of background and pre-seismic signals, were compared. Differences in the frequency content of pre-seismic sferics and geoacoustic impulses were found. The revealed features of pre-seismic signals in the future can be used in the design of systems for monitoring, forecasting and prevention of natural disasters. The research was supported by Russian Science Foundation (project No. 18-11-00087).