Abstract Recent 5G-Advanced cellular specifications introduce several positioning enhancements, including carrier phase measurements that enable high-precision 3D localization at the accuracy scale of used radio frequency (RF) wavelength. Besides localization, in numerous use cases from extended reality (XR) headsets to industrial automation and heavy machines, accurate knowledge of the device 3D orientation is of paramount importance together with low-latency operation. In this paper, utilizing multi-sensor carrier phase and Doppler measurements, we address high-precision joint tracking of device 3D location and orientation, where the full device state can be directly estimated at the network side, thus enabling very low latency and response times for possible device-related network actions. The proposed tracking approach builds on extended Kalman filter framework and is supplemented with a particle filter solution which handles the challenging integer ambiguity problem and maintains synchronization between the network and device under clock drifting. Besides tracking the user device orientation with conventional yaw, pitch and roll angles, also quaternion-based tracking approach is considered. Furthermore, multi-frequency carrier phase and Doppler measurements through carrier aggregation are addressed to further improve the performance. Based on numerical evaluations, we show that the proposed 3D location and orientation tracking achieves the derived theoretical performance bounds and reaches sub-centimeter and sub-degree accuracy for position and orientation estimation, respectively.
Saikko et al. (Thu,) studied this question.