A Universal Neural Network–Based Infrasound Event Classifier
Fredric M. Ham, Ranjan Acharyya · 2006
Infrasound is a longitudinal pressure wave [1-4]. The characteristics of these waves are similar to audible acoustic waves but the frequency range is far below what the human ear can detect. The typical frequenc y ran ge is from 0.01 to 10 Hz (Figure 3 .1). Natur e is an incredible creator of infrasonic signals that can emanate from sources such as volcano eruptions, earthquakes, severe weather, tsunamis, meteors (bolides), gravity waves, microbaroms (infrasound radiated from ocean waves), surf, mountain ranges (mountain associated waves), avalanches, and auroral waves to name a few. Infrasound can also result from man-made events such as mining blasts, the space shuttle, high-speed aircraft, artillery fire, rockets, vehicles, and nuclear events. Because of relatively low atmospheric absorption at low frequencies, infrasound waves can travel long distances in the Earth’s atmosphere and can be detected with sensitive ground-based sensors. An integral part of the comprehensive nuclear test ban treaty (CTBT) international monitoring system (IMS) is an infrasound network system [3]. The goal is to have 60 34 Signal and Image Processing for Remote Sensing infrasound arrays operational worldwide over the next several years. The main objective of the infrasound monitoring system is the detection and verification, localization, and classification of nuclear explosions as well as other infrasonic signals-of-interest (SOI). Detection refers to the problem of detecting an SOI in the presence of all other unwanted sources and noises. Localization deals with finding the origin of a source, and classification deals with the discrimination of different infrasound events of interest. This chapter concentrates on the classification part only.