Darren Griffiths, Mohammed Jahangir, Jithin Kannanthara, Gwynfor Donlan, Chris J. Baker, Michail Antoniou, Yeshpal Singh
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引用次数: 0
摘要
无人机在各个领域的应用和使用都在不断增加,尤其是在民用方面。这种日益增长的威胁要求在城市环境中进行可靠的无人机监控。雷达显然是最佳选择,因为它能在任何天气条件下探测到一定范围内的小型物体。本文探讨了如何使用 L 波段网络雷达对 S-UAS 目标进行城市感知。来自 S-UAS 的微小回波对同步性提出了更高要求,而同步性是高性能网络雷达的根本关键。通过理论和实验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回波的同步数据处理工具。此外,还在模拟和实际现场试验中使用双稳态 L 波段凝视雷达实现了无人机探测,并计算和分析了信噪比和探测性能。经过更新的双静态凝视雷达直接信号同步方法表明,它对 S-UAS 目标的信噪比和定位精度与单静态凝视雷达相当。
Fully digital, urban networked staring radar: Simulation and experimentation
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.
期刊介绍:
IET Radar, Sonar & Navigation covers the theory and practice of systems and signals for radar, sonar, radiolocation, navigation, and surveillance purposes, in aerospace and terrestrial applications.
Examples include advances in waveform design, clutter and detection, electronic warfare, adaptive array and superresolution methods, tracking algorithms, synthetic aperture, and target recognition techniques.