Shock Wave and Muzzle Blast Identification Techniques Utilizing Temporal and Spectral Aspects of Gunshot Signal

被引:0
|
作者
Nimmy, Pathrose [1 ]
Rajesh, K. R. [1 ]
Nimmy, Mathew [1 ]
Vishnu, S. [1 ]
机构
[1] Govt India Vellayambalam, Minist Commun & Informat Technol, Sci Soc, Ctr Dev Advance, Thiruvananthapuram, Kerala, India
来源
2018 IEEE RECENT ADVANCES IN INTELLIGENT COMPUTATIONAL SYSTEMS (RAICS) | 2018年
关键词
Shock Wave; Muzzle Blast; Spectral Characteristics; Multipath Reflection; Reverberation; Pattern Library;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper discusses the identification of gunshot signals, making use of the signal properties, and specific patterns that defines Shock Wave and Muzzle blast. A practical gunshot signal is highly complex with a mixture of multipath reflections, reverberating signals and distortions due to environmental factors. Complementing to this complexity is the signal degradation with distance. This poses a great challenge to discriminate the gunshot signal from the unwanted signals, as the atmospheric absorption alters the spectral characteristics and pattern considerably. An effective gunshot detection system requires precise detection of gunshot signals, by adapting to the signal variations in an uncertain environment. The techniques involved in our algorithm tackle the issues of multipath reflection and reverberation effects, to identify Shock Wave and muzzle blast in a signal with low false alarm rate and reduced computational complexity. A pattern library with suitable patterns for Shock Wave and muzzle blast signals is also constructed for accurate identification.
引用
收藏
页码:46 / 49
页数:4
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