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18 June 2012 Real-time vehicle noise cancellation techniques for gunshot acoustics
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Abstract
Acoustical sniper positioning systems rely on the detection and direction-of-arrival (DOA) estimation of the shockwave and the muzzle blast in order to provide an estimate of a potential snipers location. Field tests have shown that detecting and estimating the DOA of the muzzle blast is a rather difficult task in the presence of background noise sources, e.g., vehicle noise, especially in long range detection and absorbing terrains. In our previous work presented in the 2011 edition of this conference we highlight the importance of improving the SNR of the gunshot signals prior to the detection and recognition stages, aiming at lowering the false alarm and miss-detection rates and, thereby, increasing the reliability of the system. This paper reports on real-time noise cancellation techniques, like Spectral Subtraction and Adaptive Filtering, applied to gunshot signals. Our model assumes the background noise as being short-time stationary and uncorrelated to the impulsive gunshot signals. In practice, relatively long periods without signal occur and can be used to estimate the noise spectrum and its first and second order statistics as required in the spectral subtraction and adaptive filtering techniques, respectively. The results presented in this work are supported with extensive simulations based on real data.
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Antonio L. L. Ramos, Sverre Holm, Sigmund Gudvangen, and Ragnvald Otterlei "Real-time vehicle noise cancellation techniques for gunshot acoustics", Proc. SPIE 8359, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense XI, 835917 (18 June 2012); https://doi.org/10.1117/12.920275
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