使用多用户设备5G上行链路信号进行无源无人机定位的先融合后检测
Fuse-then-Detect for Passive UAV Localization Using Multi-UE 5G Uplink Signals
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中文总结 AI 辅助
研究利用多UE 5G上行链路信号进行无源无人机定位，针对上行链路感知挑战，设计LOS参考同步方案和联合检测器，实现亚纳秒同步，3D位置中值误差达4.84米，为无人机定位提供新的上行链路框架。
中文摘要 AI 辅助
低空无人机对空域安全、安保和隐私构成的风险日益增加。蜂窝基础设施可利用集成感知与通信（ISAC）技术在无专用雷达硬件的情况下被动感知无人机。以往大多工作基于下行链路测量采用单基地感知或双基地/多基地配置。本文提出首个上行链路框架，多个用户设备（UE）发送探测参考信号（SRS）导频，基站接收无人机散射回波。然而，上行链路SRS感知带来新挑战，如UE的振荡器和定时环路导致基站信道估计存在残余定时、频率和幅度损伤，影响无人机延迟和多普勒，且无人机回波比视距（LOS）路径和城市杂波弱，单UE传输检测不可靠。为此设计了LOS参考同步方案和联合检测器。同步复用现有定时提前（TA）命令和相邻时刻共轭积去除残余，无需额外信令。检测器搜索共享3D状态空间并跨UE累积证据，利用归一化对比度和双基地几何结构。在杂乱城市场景的频率范围1（FR1）用四个行人UE和100MHz 5G新无线电（NR）波形评估该框架，实现了亚纳秒同步和4.84米的3D位置中值误差。
英文摘要
Low-altitude uncrewed aerial vehicles (UAVs) can pose growing risks to airspace safety, security, and privacy. Cellular infrastructure can passively sense them without dedicated radar hardware by exploiting integrated sensing and communication (ISAC) technology. Most prior work exploits monostatic sensing or bistatic/multistatic configurations based on downlink measurements. To the best of our knowledge, this paper presents the first uplink framework, where multiple user equipments (UEs) transmit sounding reference signal (SRS) pilots and the base station (BS) receives the UAV-scattered echoes. Sensing from uplink SRS, however, introduces new challenges. Each UE has its own oscillator and timing loop, so the channel estimate at the BS carries residual timing, frequency, and amplitude impairments that corrupt the UAV delay and Doppler. Moreover, the UAV echo is weaker than both the line-of-sight (LOS) path and urban clutter, so detection from a single UE transmission is not reliable. We address these challenges by designing a LOS-referenced synchronization scheme and a joint detector. The synchronization reuses the existing timing advance (TA) command and an adjacent-occasion conjugate product to remove the residuals without additional signaling. Then the detector searches a shared 3D state space and accumulates evidence across UEs. It leverages a normalized contrast that exploits the bistatic geometry. We evaluate the framework in a cluttered urban scene at frequency range 1 (FR1) with four pedestrian UEs and a 100 MHz 5G New Radio (NR) waveform. The proposed pipeline achieves sub-nanosecond synchronization and a 4.84 m median 3D position error.
发表机构
- University of California San Diego（加利福尼亚大学圣地亚哥分校）
- Samsung Research America（三星美国研究所）
机构由 AI 辅助整理，请以论文原文为准。
