Filtering and extracting features from infrasound data

There are many reasons for using infrasound, i.e. low frequency sound, to monitor various events. Inherent features like its long-distance propagation and the use of simple, ground based equipment in very flexible system are some. The disadvantage is that it is a slow system due to the speed of sound. In this paper we try to show that there are several other advantages if one can extract all the features of the signal. In this way it is hoped that we can get a fingerprint of the event that caused the infrasound. Rayleigh waves and sound from epicentre may be obtained for earthquakes, pressure pulses and electrojets from aurora, core radius and funnel shape from tornados, etc. All these possibilities are suggestive for further R&D of the infrasound detection systems