Due to cost reduction and device miniaturization, amateur drones are now widely used in numerous civilian and commercial applications. However, the abuse of amateur drones has resulted in emerging threats to personal privacy and public security. To alleviate these threats, we design an acoustic-based surveillance system, which can achieve the capacity of amateur drones detection and localization with 24/7 (24 hours per day and 7 days per week under normal circumstances) availability. In the designed system, a detection fusion algorithm and a TDOA estimation algorithm based on the Bayesian filter are applied to improve the performance of drone detection and localization. Field experiments are carried out, and the results demonstrate that the designed system can detect and locate an amateur drone in real time with high accuracy and 24/7 availability.

中文翻译：

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用于业余无人机检测和定位的基于声学的监视系统

由于成本降低和设备小型化，业余无人机现在广泛用于众多民用和商业应用。然而，业余无人机的滥用已导致对个人隐私和公共安全的新威胁。为了减轻这些威胁，我们设计了一个基于声学的监视系统，它可以实现业余无人机检测和定位的能力，24/7（正常情况下每天 24 小时和每周 7 天）可用。在设计的系统中，应用基于贝叶斯滤波器的检测融合算法和TDOA估计算法来提高无人机检测和定位的性能。进行了现场实验，结果表明设计的系统可以实时检测和定位业余无人机，具有高精度和 24/7 可用性。