标题： 通过无线电频率指纹识别跟踪UWB设备是可能的 显示英文标题

标题： Tracking UWB Devices Through Radio Frequency Fingerprinting Is Possible

摘要： 超宽带（UWB）是一种先进的技术，专为需要厘米级定位的应用而设计。 其被智能手机制造商广泛采用自然引发了安全和隐私方面的担忧。 成功地将射频指纹（RFF）应用于UWB可以实现物理层安全，但也可能允许对设备的不当跟踪。 本文的目的是探讨将RFF应用于UWB的可行性，并研究该技术在不同环境中的泛化能力。 我们使用现成的UWB设备，通过控制设备位置的变化收集了一个真实的数据库。 此外，我们开发了一个改进的深度学习流程，以从信号数据中提取硬件签名。 在稳定条件下，提取的RFF准确率超过99%。 尽管在变化更大的环境中准确率会下降，但我们仍然在未训练的地点获得了高达76%的准确率。 显示英文摘要

摘要： Ultra-wideband (UWB) is a state-of-the-art technology designed for applications requiring centimeter-level localization. Its widespread adoption by smartphone manufacturer naturally raises security and privacy concerns. Successfully implementing Radio Frequency Fingerprinting (RFF) to UWB could enable physical layer security, but might also allow undesired tracking of the devices. The scope of this paper is to explore the feasibility of applying RFF to UWB and investigates how well this technique generalizes across different environments. We collected a realistic dataset using off-the-shelf UWB devices with controlled variation in device positioning. Moreover, we developed an improved deep learning pipeline to extract the hardware signature from the signal data. In stable conditions, the extracted RFF achieves over 99% accuracy. While the accuracy decreases in more changing environments, we still obtain up to 76% accuracy in untrained locations.