标题： 利用5G NR雷达检测空中物体 显示英文标题

标题： Detecting Airborne Objects with 5G NR Radars

摘要： 将5G新空口（5G NR）网络集成传感能力提供了一个机会，可以在不需要专用雷达的情况下检测空气中的物体。 本文研究了使用标准化的定位参考信号（PRS）在城市微（UMi）和城市宏（UMa）传播环境中检测无人机的可行性。 实现了完整的5G NR雷达处理链，包括杂波抑制、角度和范围估计以及三维位置重建。 仿真结果显示性能强烈依赖于传播环境。 由于严重的杂波，5G NR雷达在UMi中的漏检率最高可达16%。 定位误差随目标距离增加而增加，在UMa场景和较高无人机高度下会产生更大的误差。 特别是，系统在UMi环境中实现小于4米的位置误差，在UMa环境中实现小于8米的位置误差。 仿真平台已被作为开源软件发布，以支持综合感知和通信（ISAC）系统的可重复研究。 显示英文摘要

摘要： The integration of sensing capabilities into 5G New Radio (5G NR) networks offers an opportunity to enable the detection of airborne objects without the need for dedicated radars. This paper investigates the feasibility of using standardized Positioning Reference Signals (PRS) to detect UAVs in Urban Micro (UMi) and Urban Macro (UMa) propagation environments. A full 5G NR radar processing chain is implemented, including clutter suppression, angle and range estimation, and 3D position reconstruction. Simulation results show that performance strongly depends on the propagation environment. 5G NR radars exhibit the highest missed detection rate, up to 16%, in UMi, due to severe clutter. Positioning error increases with target distance, resulting in larger errors in UMa scenarios and at higher UAV altitudes. In particular, the system achieves a position error within 4m in the UMi environment and within 8m in UMa. The simulation platform has been released as open-source software to support reproducible research in integrated sensing and communication (ISAC) systems.