Indirect weapon fire from mortars or artillery generates an impulsive sound that propagates radially outwards as a spherically expanding wavefront from the point of fire. This point of fire can be located by triangulating the directions-of-arrival of the incident wavefront at two (or more) widely separated sensor nodes situated in the far field. The method is demonstrated using real data recorded during a live artillery fire exercise. Next, the sensor data containing the impulsive sound signal from each artillery firing event are mixed with the acoustic noise data recorded on a tactical unmanned aerial vehicle (TUAV). The mixed data are dominated by the TUAV platform noise which masks the impulsive sound signal. By processing the mixed data with a harmonic suppression filter followed by a false alarm discriminator, it is demonstrated that impulsive sound signals associated with artillery fire can be detected with negligible false alarm rates in the presence of TUAV platform noise. Finally, acoustic sensor data are recorded and processed for a direct fire experiment. A direct fire weapon (rifle) produces an impulsive sound (muzzle blast) associated with the firing of a bullet. If the bullet travels at a supersonic speed, another impulsive sound (a ballistic shock wave) is generated by the passage of the bullet. If the ballistic shock wave is received by a high-frequency piezoelectric sensor, the amplitude and duration of the signal waveform can be used to estimate the calibre and miss distance of the bullet. The effectiveness of a feature-based method for classification between 5.56-mm and 7.62-mm rounds is demonstrated using real data.
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