DocumentCode
693526
Title
Acoustic shockwave-based bearing estimation
Author
Sallai, Janos ; Volgyesi, Peter ; Ledeczi, Akos ; Pence, Ken ; Bapty, Ted ; Neema, Sandeep ; Davis, J.
Author_Institution
Inst. for Software Integrated Syst., Vanderbilt Univ., Nashville, TN, USA
fYear
2013
fDate
8-11 April 2013
Firstpage
217
Lastpage
228
Abstract
The paper presents a smartphone-based shooter localization system. As muzzle blasts are difficult to detect at longer distances and consequently present higher false detection rates, the system relies on shockwaves only. Each sensor uses four microphones to detect the Angle of Arrival and the length of the shockwave. This information, along with the sensor´s own GPS coordinates, are shared among nearby smartphones. Assuming a known weapon type, it then proceeds to estimate the two possible projectile trajectory candidates for each sensor that are consistent with the observations in the horizontal plane of the sensors. A simple clustering algorithm identifies the correct projectile trajectory relying on as few as two sensors. The trajectory is then used to estimate the bearing to the shooter relative to each sensor. The paper presents the overall system architecture, the design of the sensor node that interfaces with the smartphone, the trajectory and bearing estimation algorithms, and the evaluation of the system based on a field experiment.
Keywords
Global Positioning System; direction-of-arrival estimation; microphones; pattern clustering; projectiles; shock waves; smart phones; wireless sensor networks; GPS coordinates; acoustic shockwave-based bearing estimation; angle of arrival detection; clustering algorithm; microphones; projectile trajectory; shockwave length detection; smartphone-based shooter localization system; Acoustics; Global Positioning System; Microphones; Projectiles; Trajectory; Universal Serial Bus; Wireless communication; Sensor networks; acoustic source localization; data fusion; shooter localization;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Processing in Sensor Networks (IPSN), 2013 ACM/IEEE International Conference on
Conference_Location
Philadelphia, PA
Type
conf
DOI
10.1109/IPSN.2013.6917564
Filename
6917564
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