کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
383731 | 660832 | 2014 | 8 صفحه PDF | دانلود رایگان |
• Pattern recognition approach to shock wave and muzzle blast classification.
• Two-stage shock wave and muzzle blast recognition.
• Independent from ballistic model, wavelet based signature representation.
• Approximation coefficients thresholding for classification purposes.
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.
Journal: Expert Systems with Applications - Volume 41, Issue 11, 1 September 2014, Pages 5097–5104