Wavelet based shock wave and muzzle blast classification for different supersonic projectiles

摘要

The article presents a pattern recognition approach to acoustic shock wave and muzzle blast detection. Gunshot signatures are divided into multiple classes, given by combination of 3 types of supersonic weapons of different caliber: 7.62 mm, 5.56 mm and 9 mm and 3 types of acoustic events: shock wave, muzzle blast and reflections. The classification is performed on wavelet compressed 100 μs time frames. The experiment shows that the choice of a fitting wavelet base is crucial for the quality of recognition.