Measurements of small-caliber ballistic shock waves in air

Stoughton, Roland

doi:10.1121/1.419904

Cited by 54 publications

(36 citation statements)

References 13 publications

(25 reference statements)

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“…Fansler's work gives a good idea of the ideal muzzle blast pressure wave without contamination from echoes or propagation effects [4]. Experiments with greater distances from the muzzle were conducted by Stoughton [18]. The measurements of the ballistic shockwaves using calibrated pressure transducers at known locations, measured bullet speeds, and miss distances of 3 -55 meters for 5.56 mm and 7.62 mm projectiles were made.…”

Section: Related Workmentioning

confidence: 99%

Shooter localization and weapon classification with soldier-wearable networked sensors

Völgyesi

Balogh

Nádas

et al. 2007

Proceedings of the 5th International Conference on Mobile Systems, Applications and Services

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The paper presents a wireless sensor network-based mobile countersniper system. A sensor node consists of a helmetmounted microphone array, a COTS MICAz mote for internode communication and a custom sensorboard that implements the acoustic detection and Time of Arrival (ToA) estimation algorithms on an FPGA. A 3-axis compass provides self orientation and Bluetooth is used for communication with the soldier's PDA running the data fusion and the user interface. The heterogeneous sensor fusion algorithm can work with data from a single sensor or it can fuse ToA or Angle of Arrival (AoA) observations of muzzle blasts and ballistic shockwaves from multiple sensors. The system estimates the trajectory, the range, the caliber and the weapon type. The paper presents the system design and the results from an independent evaluation at the US Army Aberdeen Test Center. The system performance is characterized by 1-degree trajectory precision and over 95% caliber estimation accuracy for all shots, and close to 100% weapon estimation accuracy for 4 out of 6 guns tested. Keywords: Sensor networks, data fusion, acoustic source localization, weapon classification, caliber estimation Acknowledgments: The Darpa IpTO ASSIST program has supported this research. We'd like to express our gratitude to Brian A. Weiss, Craig Schlenoff and the US Army Aberdeen Test Center who carried out the independent evaluation of the system. We are also grateful to Miklós Maróti, Gyula Simon, Branislav Kusý, Béla Fehér, Sebestyén Dóra, Ken Pence, Ted Bapty, Jason Scott and the Nashville Police Academy for their contributions. We'd like to thank our shepherd, Dan Siewiorek for his constructive comments. Categories and Subject Descriptors

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Section: Related Workmentioning

confidence: 99%

Shooter localization and weapon classification with soldier-wearable networked sensors

Völgyesi

Balogh

Nádas

et al. 2007

Proceedings of the 5th International Conference on Mobile Systems, Applications and Services

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“…The non-linear propagation behavior of the shock wave will gradually lose its characteristic "N" wave shape and become a less abrupt "S" shaped pressure disturbance due to nonlinear dispersion [5].…”

Section: Acoustical Issuesmentioning

confidence: 99%

“…If a supersonic projectile's journey from the firearm to the target is more than a few tens of meters, the effects of drag-induced deceleration may need to be taken into account [4,5]. The bullet is slowed by friction with the air and due to the conversion of its kinetic energy into the acoustic shock wave.…”

Section: Ground Surfacementioning

confidence: 99%

Modeling and Signal Processing of Acoustic Gunshot Recordings

Maher

2006

2006 IEEE 12th Digital Signal Processing Workshop &Amp;amp; 4th IEEE Signal Processing Education Workshop

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Audio recordings of gunshots can provide information about the gun location with respect to the microphone(s), the speed and trajectory of the projectile, and in some cases the type of firearm and ammunition. Recordings obtained under carefully controlled conditions can be well-modeled by geometrical acoustics. Special acoustic processing systems for real time gunshot detection and localization are used by the military and law enforcement agencies for sniper detection. Forensic analysis of audio recordings is also used to provide evidence in criminal and civil cases. This paper reviews the distinctive features and limitations of acoustic gunshot analysis using DSP techniques.

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“…In the existing literature, the initial establishment of the theory of shockwave model provides the basis for the prediction of the overpressure and the drawing of the contour line of the shockwave overpressure field [1]. Previous studies showed that the test of the shockwave overpressure field to obtain the overpressure value of the sensor array at different points and draw the contour lines by the interpolation algorithm was mainly based on the electric method [2]. Interpolation compensates for the deficiency of spatial observation data points.…”

Section: Introductionmentioning

confidence: 99%

Cooperation of the Spatial Interpolation Algorithm for the Contour Map of the Shockwave Overpressure Field

Yong-li¹,

Han²,

Liu³

et al. 2017

JESTR

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Traditionally, the peak overpressures of multi-point shockwave are obtained through the sensor array by using the electrometric method, and then the surface interpolation is carried out by the mathematical model to draw the contour lines of the shockwave overpressure field. The cross-validation method of the mean absolute error (MAE), mean relative error (MRE), and root mean square error (RMSE) was proposed in this study to achieve high precision and effective interpolation of the contour lines. The quantitative test of Kinney-Graham Formula was verified, and the peak overpressures of the multi-point shockwave of a 7.62-mm caliber gun and a naval gun were obtained through the sensor array based on polar coordinate. Then, the shockwave overpressure field was interpolated by the inverse distance weighted (IDW) interpolation, the ordinary kriging interpolation(OK), the radial basis function (RBF) interpolation, and the cubic spline (CS) function interpolation, Finally, cross-validation analysis was performed on MAE, MRE, and RMSE. Results demonstrate that the MAE of the RBF interpolation is 0.038, and the MRE is 0.001. The error is smallest, the accuracy is highest, and the interpolation effect is closest to the shockwave field model. The OK interpolation is close to the RBF interpolation. The MRE of the CS interpolation is 0.254, which is relatively large. The RMSE of the IDW interpolation is 14.268, which is abnormal. The RBF interpolation is the optimal interpolation algorithm for the shockwave overpressure field, which provides a reference for the contour drawing of the shockwave overpressure field.

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Measurements of small-caliber ballistic shock waves in air

Cited by 54 publications

References 13 publications

Shooter localization and weapon classification with soldier-wearable networked sensors

Shooter localization and weapon classification with soldier-wearable networked sensors

Modeling and Signal Processing of Acoustic Gunshot Recordings

Cooperation of the Spatial Interpolation Algorithm for the Contour Map of the Shockwave Overpressure Field

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