基于5G ISAC的无人机检测与三维跟踪：在端到端O-RAN仿真测试平台上使用上行链路探测参考信号
5G ISAC-Based UAV Detection and 3-D Tracking Using Uplink Sounding Reference Signals on an End-to-End O-RAN Simulation Testbed
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中文总结 AI 辅助
该研究构建端到端O-RAN仿真测试平台，利用5G ISAC技术通过NR上行探测参考信号实现无人机检测与三维跟踪，解决仰角不可观测问题，在10Mbps通信负载下保持检测覆盖，高度估计误差达1.8米。
中文摘要 AI 辅助
集成传感与通信（ISAC）允许蜂窝基础设施在同一波形上同时为通信用户提供服务和感知功能。我们提出了一个针对低空无人机检测与三维跟踪的5G ISAC端到端O-RAN仿真测试平台，该平台由开源组件构建而成：OpenAirInterface、FlexRIC和Sionna RT，其中NR上行链路探测参考信号被重新用作无源雷达波形：gNB内部的PHY层感知阶段生成检测结果，这些结果通过自定义E2服务模型传递至扩展卡尔曼滤波器跟踪xApp，且无需修改NR标准，也无需专用感知波形。单个双基地对会导致仰角不可观测，因此跟踪器需要高度先验信息；我们通过两种独立方式消除该需求并对其进行测量：一种是提供垂直孔径的平面接收阵列，另一种是提供距离分集的第二个发射机。两种实时结果均证实了针对同一估计器的离线射线追踪研究，该研究从故意错误的初始高度收敛，在一致滤波器下达到1.8米的均方根误差，因此仰角可观测性在信号处理链和通过实时栈的端到端层面均得到确立。在并发10 Mbps上行链路通信负载下，检测覆盖范围得以保留。
英文摘要
Integrated Sensing and Communication (ISAC) lets cellular infrastructure serve communication users and sense on the same waveform. We present an end-to-end O-RAN simulation testbed for 5G ISAC targeting low-altitude UAV detection and 3-D tracking, built from open-source components: OpenAirInterface, FlexRIC and Sionna RT, in which the NR Uplink Sounding Reference Signal is repurposed as a passive radar waveform: a PHY-layer sensing stage inside the gNB produces detections that reach an Extended Kalman Filter tracking xApp over a custom E2 service model, with no change to the NR standard and no dedicated sensing waveform. A single bistatic pair leaves elevation unobservable, so the tracker needs a height prior; we remove it two independent ways and measure both - a planar receive array supplying a vertical aperture, and a second transmitter supplying range diversity. Both live results corroborate an offline ray-traced study of the same estimator, which converges from a deliberately wrong initial altitude to 1.8 m RMSE at a consistent filter, so altitude observability is established both in the signal-processing chain and end to end through the live stack. Detection coverage is preserved under a concurrent 10 Mbps uplink communications load.
