Understanding the location of ultra-wideband (UWB) tag-attached objects and people in the real world is vital to enabling a smooth cyber-physical transition. However, most UWB localization systems today require multiple anchors in the environment, which can be very cumbersome to set up. In this work, we develop XRLoc, providing an accuracy of a few centimeters in many real-world scenarios. This paper will delineate the key ideas which allow us to overcome the fundamental restrictions that plague a single anchor point from localization of a device to within an error of a few centimeters. We deploy a VR chess game using everyday objects as a demo and find that our system achieves $2.4$ cm median accuracy and $5.3$ cm $90^\mathrm{th}$ percentile accuracy in dynamic scenarios, performing at least $8\times$ better than state-of-art localization systems. Additionally, we implement a MAC protocol to furnish these locations for over $10$ tags at update rates of $100$ Hz, with a localization latency of $\sim 1$ ms.

翻译：理解现实世界中携带超宽带（UWB）标签的物体和人的位置，对于实现顺畅的物理-数字过渡至关重要。然而，当前多数UWB定位系统需要在环境中部署多个锚点，这往往导致安装过程极为繁琐。本文开发了XRLoc系统，可在多种实际场景中实现厘米级精度。本文将阐述关键思想，这些思想使我们能够克服困扰单锚点定位系统的基本限制，将设备定位误差控制在厘米级。我们利用日常物品演示了一个VR国际象棋游戏，实验表明，在动态场景下，该系统达到了$2.4$厘米的中位精度和$5.3$厘米的$90^\mathrm{th}$百分位精度，性能比现有最优定位系统至少提升$8$倍。此外，我们实现了一种MAC协议，可在$100$ Hz更新速率下为超过$10$个标签提供定位服务，定位延迟约为$\sim 1$ ms。