Dynamic Anchor Selection and Real-Time Pose Prediction for Ultra-wideband Tagless Gate

TL;DR

DynaPose addresses the challenge of reliable proximity sensing with UTG by integrating LOS NLOS classification from CIR and IMU data with dynamic anchor selection and pose prediction. The system deploys an eCIR updater to minimize data transfer, uses Graham Scan based anchor selection, and CNN LSTM based pose prediction to deliver real time LOC and door opening decisions. It achieves high LOS NLOS accuracy of 0.984, pose accuracy of 0.961, and substantial DL TDoA improvements in NLOS, demonstrating practical feasibility on smartphone and UWB hardware. The work advances UWB proximity services by enabling reliable gate access without device taps, with potential applications in office buildings and transit environments.

Abstract

Ultra-wideband (UWB) is emerging as a promising solution that can realize proximity services, such as UWB tagless gate (UTG), thanks to centimeter-level localization accuracy based on two different ranging methods such as downlink time-difference of arrival (DL-TDoA) and double-sided two-way ranging (DS-TWR). The UTG is a UWB-based proximity service that provides a seamless gate pass system without requiring real-time mobile device (MD) tapping. The location of MD is calculated using DL-TDoA, and the MD communicates with the nearest UTG using DS-TWR to open the gate. Therefore, the knowledge about the exact location of MD is the main challenge of UTG, and hence we provide the solutions for both DL-TDoA and DS-TWR. In this paper, we propose dynamic anchor selection for extremely accurate DL-TDoA localization and pose prediction for DS-TWR, called DynaPose. The pose is defined as the actual location of MD on the human body, which affects the localization accuracy. DynaPose is based on line-of-sight (LOS) and non-LOS (NLOS) classification using deep learning for anchor selection and pose prediction. Deep learning models use the UWB channel impulse response and the inertial measurement unit embedded in the smartphone. DynaPose is implemented on Samsung Galaxy Note20 Ultra and Qorvo UWB board to show the feasibility and applicability. DynaPose achieves a LOS/NLOS classification accuracy of 0.984, 62% higher DL-TDoA localization accuracy, and ultimately detects four different poses with an accuracy of 0.961 in real-time.

Figures (17)

• Figure 1: The operation of UTG based on the two different UWB ranging technologies.
• Figure 2: The normal and unexpected operations of UTG. The opening and closing of gate are colored in green and red.
• Figure 3: Two different ranging methods using UWB.
• Figure 4: The example of CIR data including channel diagnostics. The FP_INDEX and maxNoise are 747 and 1409.
• Figure 5: The converted distances from TDoA measurements of the LOS (red) and NLOS condition (blue).