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This paper introduces an improved spectral subtraction based algorithm for real-time noise cancellation, applied to gunshot acoustical signals. The derivation is based on the fact that, in practice, relatively long periods without gunshot signals occur and the background noise can be modeled as being short-time stationary and uncorrelated to the impulsive gunshot signals. Moreover, gunshot signals, in general, have a spiky autocorrelation while typical vehicle noise, or related, is periodic and exhibits a wider autocorrelation. The Spectral Suppression algorithm is applied using the pre-filtering approach, as opposed to post-filtering which requires a priori knowledge of the direction of arrival of the signals of interest, namely, the Muzzle blast and the Shockwave. The results presented in this work are based on a dataset generated by combining signals from real gunshots and real vehicle noise.

A Spectral Subtraction Based Algorithm for Real-time Noise Cancellation with Application to Gunshot Acoustics