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A Surveillance System for Drone Localization and Tracking Using Acoustic Arrays

机译:使用声阵列的无人机定位和跟踪监视系统

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The wide proliferation of drones has posed great threats to personal privacy and public security, which makes it urgent to monitor the drones in the sensitive areas. Drone surveillance using acoustic arrays, as a promising method, could localize and track the drones effectively. In this paper, we develop a systematic method for drone localization and tracking by using acoustic arrays. Specifically, we develop a time difference of arrival (TDOA) estimation algorithm based on Gauss priori probability density function to overcome the multipath effect and the low signal-to-noise ratio (SNR), and design a localization method by making full use of the TDOA estimation results, followed by tracking the drone by Kalman filter. Finally, field experiments are carried out to verify the effectiveness and performance of the proposed methods. The results show that they can achieve good performance in drone localization and tracking.
机译:无人机的广泛扩散对个人隐私和公共安全构成了巨大威胁,因此迫切需要对敏感地区的无人机进行监控。作为一种有前途的方法,使用声阵列的无人机监视可以有效地定位和跟踪无人机。在本文中,我们开发了一种使用声学阵列进行无人机定位和跟踪的系统方法。具体来说,我们开发了一种基于高斯先验概率密度函数的到达时间差(TDOA)估计算法,以克服多径效应和低信噪比(SNR)的问题,并充分利用该算法来设计定位方法TDOA估计结果,然后通过卡尔曼滤波器跟踪无人机。最后,进行现场实验以验证所提出方法的有效性和性能。结果表明,它们可以在无人机定位和跟踪中取得良好的性能。

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