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Effective direction of arrival estimation of gunshot signals from an in-flight unmanned aerial vehicle

机译:空中无人驾驶飞机发出的枪响信号的有效到达方向估计

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Spotting a shooter from a drone has been the subject of great interest lately due to its many applications in the fields of defense and security and law enforcement. Using a drone can be an effective way to detect potential threats in many real-life scenarios. Nevertheless, acoustic signals recorded from a drone usually exhibit a very low SNR, mainly due to the distance to the source and the proximity of the sensors to the propellers. This is a serious limiting factor and, therefore, the use of signal enhancement techniques is required. This work addresses the problem of determining the Direction-of-Arrival (DoA) of the muzzle blast, captured using a planar microphone array mounted on a commercial DJI PHANTOM 4 drone in flight. This new shooter localization method that relies solely on detecting and estimating the DoA of the muzzle blast. However, the typical low SNR in this scenario requires the use of preprocessing techniques, such as signal clipping and median filtering, to enhance the signal of interest (muzzle blast). In addition, we employ a recently introduced improved data selection DoA estimation method suitable for gunshot signals recorded from a low to medium altitude mobile aerial platform. Positive results achieved indicate that this approach is effective and of practical interest.
机译:从无人机上找到射手是近来引起人们极大兴趣的主题,因为它在国防,安全和执法领域有许多应用。在许多现实生活中,使用无人机可能是检测潜在威胁的有效方法。尽管如此,从无人机记录的声音信号通常显示出非常低的SNR,这主要是由于到源的距离以及传感器与螺旋桨的距离。这是一个严重的限制因素,因此,需要使用信号增强技术。这项工作解决了确定炮口爆炸的到达方向(DoA)的问题,该炮口是使用安装在飞行中的商用DJI PHANTOM 4无人机上的平面麦克风阵列捕获的。这种新的射手定位方法完全依赖于检测和估计枪口爆炸的DoA。但是,在这种情况下,典型的低SNR需要使用预处理技术(例如信号削波和中值滤波)来增强目标信号(炮口爆炸)。此外,我们采用了最近推出的改进的数据选择DoA估计方法,该方法适用于从低高度到中高度移动式空中平台记录的枪声信号。取得的积极成果表明,这种方法是有效的,具有实际意义。

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