Acoustic Localisation of Gunshots in the Presence of Obstacles

A. Sinha, Tushar Singh
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Abstract

Acoustic localization of gunshots is of interest for protecting security camps in contested forests, increasing soldiers’ situation awareness in ambushes, as well as in guarding cities. All these scenarios are also fraught with obstacles coming in the path of acoustic waves. We present a computational study of the effect of obstacles on the accuracy of localization of point sound sources like gunshots. The two-dimensional linearized Euler equations are solved with the dispersion relation preserving scheme. The localization is performed using the wavefront curvature method based on pressure signatures recorded at three virtual microphones. We report at most 8◦ of error in the estimated bearing angle of the source across a range of practical values of five parameters – viz. the location and size of the obstacle, and the size, orientation and location of the sensor array relative to the source. This level of error may be quite acceptable in the scenarios considered. On the other hand, the range error is much more severe, exceeding 100% of the true range in a few cases. In the scenarios considered, the bearing angle estimate is much more critical than the range estimate. Overall, we conclude that acoustic localization approaches are quite robust in the presence of obstacles.
障碍物存在时枪声的声学定位
枪声的声学定位对于保护有争议的森林中的安全营地,提高士兵在伏击中的情况意识以及守卫城市都很有意义。所有这些场景都充满了声波路径上的障碍。本文研究了障碍物对枪响等点声源定位精度的影响。用色散关系保持格式求解二维线性化欧拉方程。采用基于三个虚拟传声器记录的压力信号的波前曲率方法进行定位。在五个参数的实际值范围内,即障碍物的位置和大小,以及相对于源的传感器阵列的大小,方向和位置,我们报告了源的估计方位角最多8◦的误差。在考虑的场景中,这种级别的错误可能是完全可以接受的。另一方面,距离误差更为严重,在少数情况下超过了真实距离的100%。在考虑的情况下,方位角估计比距离估计更为关键。总的来说,我们得出的结论是,在存在障碍物的情况下,声学定位方法是相当稳健的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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