The application and uses of drones in all areas are continuously rising, especially in civilian use cases. This increasing threat requires reliable drone surveillance in urban environments. Radar is the obvious candidate with its ability to detect small objects at range, in all weather conditions. The use of an L-band networked radar for urban sensing of S-UAS targets is explored. Small echoes from S-UAS places a premium on synchronisation, which is the fundamental key for high performance networked radar. The effect of timing errors on the operation of the network radar is investigated theoretically and experimentally, and the processing tools for synchronising data based on the direct signal returns of the transmitter are developed. Also, drone detection using bistatic L-band staring radar is achieved both in simulation and then in real field trials where the SNR and detection performance are computed and analysed. The updated direct signal synchronisation method for bistatic staring radar is shown to provide comparable SNR and positional accuracy for S-UAS targets as the monostatic staring radar.

中文翻译：

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全数字化城市网络凝视雷达：模拟和实验

无人机在各个领域的应用和使用不断上升，特别是在民用领域。这种日益严重的威胁需要在城市环境中进行可靠的无人机监控。雷达是明显的候选者，因为它能够在各种天气条件下探测远处的小物体。探索了使用 L 波段网络雷达对 S-UAS 目标进行城市感知。S-UAS 发出的小回波非常重视同步，这是高性能网络雷达的基本关键。从理论上和实验上研究了定时误差对网络雷达运行的影响，并开发了基于发射机直接信号返回的同步数据处理工具。此外，在模拟和实际现场试验中都实现了使用双基地 L 波段凝视雷达的无人机检测，其中计算和分析了信噪比和检测性能。更新后的双基地凝视雷达直接信号同步方法可为 S-UAS 目标提供与单基地凝视雷达相当的 ​​SNR 和位置精度。