Orientation and Location Tracking of XR Devices: 5G Carrier Phase-Based Methods

Abstract

Accurate knowledge of the three-dimensional (3D) orientations and 3D locations of the user devices, such as wearable glasses, is of paramount importance in different extended reality (XR) use cases and applications. In this article, we address the corresponding six degrees-of-freedom (6DoF) tracking challenge of 5G-empowered XR devices. We describe a new uplink (UL) carrier phase measurements based estimation approach, allowing for low-latency 3D orientation and 3D location tracking directly at the 5G network base-stations or gNodeBs (gNBs). extended Kalman filter (EKF) based practical signal processing algorithms are described while also the applicable Cramér-Rao lower-bounds (CRLBs) are derived and presented. Also, the related aspect of over-the-air estimation of the XR headset antenna constellation or antenna geometry is addressed. Additionally, the important practical challenges related to user equipment (UE) clock drifting as well as integer ambiguities in carrier phase based methods are both considered. Finally, an extensive set of numerical results is provided in an example indoor factory like environment, covering both 3.5 GHz and 28 GHz network deployments. The obtained results demonstrate the feasibility of continuous 6DoF tracking through the proposed approach, with root mean squared error (RMSE) accuracies below one degree for the 3D orientation and below one centimeter for the 3D location, respectively. The results also demonstrate that UE clock drifting and carrier phase integer ambiguities can both be efficiently estimated and tracked, as part of the overall proposed concept and methods.