Understanding Distance Shooting and the Type of Firearm from the Analysis of Gunshot Sounds (original) (raw)
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Gunshot Acoustics: Pistol vs. Revolver
2017
Audio forensic investigations may require interpretation of recordings containing gunshot sounds. These sounds are notable because of their impulsive nature: very high sound pressure and very short duration compared to other sounds relevant to forensic analysis. In this paper we examine the acoustical characteristics of muzzle blast sounds from two handguns: a Glock 19 pistol and a Ruger SP101 revolver. The muzzle blast sound of each handgun was recorded at several azimuth angles between 0 and 180 degrees with respect to the barrel using a quasi-anechoic methodology. Compared to the pistol, the revolver exhibits a more complicated acoustical pattern due to sound emanation from two sources: the cylinder-barrel gap and the muzzle.
Determining the Muzzle Blast Duration and Acoustical Energy of Quasi-Anechoic Gunshot Recordings
Journal of The Audio Engineering Society, 2016
Investigation of gunshot waveforms largely includes analyzing the muzzle blast. Generated by the combustion of gunpowder immediately after firing, these brief duration directional shock waves travel outward in all directions at the speed of sound. Features of these waveforms are analyzed to identify characteristics of a particular shot, for example, the combination of firearm type, ammunition, and orientation. This paper includes measured muzzle blast durations for several common firearms and calculation of the total acoustical energy during the muzzle blast period.
Gunshots Sound Analysis, Identification, and Impact on Hearing
Particularly, I would like to thank Prof. Rafik Goubran for his support, guidance and enlightenment through all these years and Dr. David Lo for being a wonderful colleague, supervisor and friend. Without him, the thesis would not have been possible. My thanks also go to Master Corporal Alex Saumure; recording the data was simple with him taking charge of all the logistics and his ensuring that we had all the equipment. Finally, I would like to thank my love, Chantal Boutin. I am so lucky to have you by my side.
2016
the opportunity and invaluable guidance throughout this research. His dynamism, vision, sincerity and motivation have deeply inspired me. It was a great privilege and honor to carry out my work under his guidance. I am extremely grateful for what he has offered me not only as a mentor but also as a human being. I would also like to thank him for his patience, empathy, and most importantly, understanding me as a person. My Special thanks go to Prof. Steven Shaw for his support in gunshot recordings. I am extremely grateful to Angelo Borzino, for his support in the interpretation of recorded signals. I am extending my gratitude to Tyler Davis, for his assistance during the whole period. Finally, my thanks go to my parents and all my friends and staff of this department, who has directly and indirectly, supported me to complete the research work.
Measuring Recreational Firearm Noise
Sound Vibration, 2009
Recreational use of firearms in the United States is commonplace. It is estimated that approximately one-third of households in the U.S. own firearms. 1 There are 28 million Americans who consider themselves hunters, and 13 million went hunting in 2000. 2 Participation in shooting sports without the use of properly worn hearing protection exposes participants to high levels of impulsive noise that may cause hearing loss or tinnitus (ringing in the ear). Firearms may cause permanent hearing loss even after a single or a few unprotected exposures. The present study was initiated to gain a better understanding of the noise exposure created by contemporary firearms using state-of-the-art instrumentation and to ultimately increase our knowledge and awareness of this unique noise hazard.
Wideband Audio Recordings of Gunshots: Waveforms and Repeatability
2016
For the purposes of audio forensics research we have obtained multi-channel acoustical recordings of gunshots under controlled conditions for several firearms. The recordings are made using an elevated platform and an elevated spatial array of microphones to provide quasi-anechoic directional recordings of the muzzle blast. The consistency and repeatability of gunshot sounds are relevant to many areas of forensic analysis. This paper includes a description of the recording process and a summary comparison of the acoustical waveforms obtained from ten successive shots from the same firearm by an experienced marksman. Practical examples and applications are presented.
Recording anechoic gunshot waveforms of several firearms at 500 kilohertz sampling rate
2016
Acoustic gunshot signals consist of a high amplitude and short duration impulsive sound known as the muzzle blast and the shock wave. This experiment involved documenting gunshot muzzle blast sounds produced by eight commonly used firearms including Remington 870, Colt 45, Glock 19 with 9mm ammunition, Glock 23, Sig 239, AR15, 22LR, and Ruger SP 101 with 357 magnum and 38 special ammunition. An elevated microphone bracket (3m above the ground) was built to achieve a quasianechoic environment for the duration of the muzzle blast. Twelve microphones (GRAS 40DP) were mounted on the bracket in a semi-circular arc to observe the azimuthal variation of the muzzle blast. Signals were recorded using LabVIEW. Similarities and differences among waveforms are presented.
Measurements, Analysis, Classification, and Detection of Gunshot and Gunshot-like Sounds
Sensors
Gun violence has been on the rise in recent years. To help curb the downward spiral of this negative influence in communities, machine learning strategies on gunshot detection can be developed and deployed. After outlining the procedure by which a typical type of gunshot-like sounds were measured, this paper focuses on the analysis of feature importance pertaining to gunshot and gunshot-like sounds. The random forest mean decrease in impurity and the SHapley Additive exPlanations feature importance analysis were employed for this task. From the feature importance analysis, feature reduction was then carried out. Via the Mel-frequency cepstral coefficients feature extraction process on 1-sec audio clips, these extracted features were then reduced to a more manageable quantity using the above-mentioned feature reduction processes. These reduced features were sent to a random forest classifier. The SHapley Additive exPlanations feature importance output was compared to that of the mean...
Advancing Forensic Analysis of Gunshot Acoustics
Journal of The Audio Engineering Society, 2015
This paper describes our current work to create the apparatus and methodology for scientific and repeatable collection of firearm acoustical properties, including the important direction-dependence of each firearm’s sound field. Gunshot acoustical data is collected for a wide range of firearms using an elevated shooting platform and an elevated spatial array of microphones to allow echo-free directional recordings of each firearm’s muzzle blast. The results of this proposed methodology include a standard procedure for cataloging firearm acoustical characteristics, and a database of acoustical signatures as a function of azimuth for a variety of common firearms and types of ammunition.
Precision and accuracy of acoustic gunshot location in an urban environment
ArXiv, 2021
The muzzle blast caused by the discharge of a firearm generates a loud, impulsive sound that propagates away from the shooter in all directions. The location of the source can be computed from time-of-arrival measurements of the muzzle blast on multiple acoustic sensors at known locations, a technique known as multilateration. The multilateration problem is considerably simplified by assuming straight-line propagation in a homogeneous medium, a model for which there are multiple published solutions. Live-fire tests of the ShotSpotter gunshot location system in Pittsburgh, PA were analyzed off-line under several algorithms and geometric constraints to evaluate the accuracy of acoustic multilateration in a forensic context. Best results were obtained using the algorithm due to Mathias, Leonari and Galati under a two-dimensional geometric constraint. Multilateration on random subsets of the participating sensor array show that 96% of shots can be located to an accuracy of 15 m or bette...