TY - GEN
T1 - A Practical TDOA-Based Method for UWB Anchor Localization
AU - Zhang, Xinchi
AU - Wang, Jiale
AU - Xia, Ming
AU - Yue, Ziwei
AU - Zhang, Deyou
AU - Shi, Chuang
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - This paper presents a practical TDOA-based method for UWB anchor localization, aiming to simplify the process of determining anchor positions, reduce costs, and improve efficiency. By utilizing a small number of tag position coordinates and the TDOA information between anchors and tags, and by introducing a weighted least squares approach, this method can quickly and effectively solve for UWB anchor coordinates even without any prior knowledge of their initial positions. Experimental results demonstrate that the proposed method can achieve positioning accuracy within 1 meter, with the rectangular trajectory demonstrating the highest stability and accuracy, as indicated by the lowest RMSE (Root Mean Square Error) and HDOP (Horizontal Dilution of Precision) values. Future research will focus on optimizing the algorithm under complex environmental conditions, integrating data from multiple sensors such as LiDAR or cameras, enhancing real-time performance, and developing user-friendly interfaces. These efforts aim to further enhance the method's robustness and practical applicability. Additionally, comparative experiments in diverse scenarios will be conducted to validate the effectiveness and applicability of the proposed approach.
AB - This paper presents a practical TDOA-based method for UWB anchor localization, aiming to simplify the process of determining anchor positions, reduce costs, and improve efficiency. By utilizing a small number of tag position coordinates and the TDOA information between anchors and tags, and by introducing a weighted least squares approach, this method can quickly and effectively solve for UWB anchor coordinates even without any prior knowledge of their initial positions. Experimental results demonstrate that the proposed method can achieve positioning accuracy within 1 meter, with the rectangular trajectory demonstrating the highest stability and accuracy, as indicated by the lowest RMSE (Root Mean Square Error) and HDOP (Horizontal Dilution of Precision) values. Future research will focus on optimizing the algorithm under complex environmental conditions, integrating data from multiple sensors such as LiDAR or cameras, enhancing real-time performance, and developing user-friendly interfaces. These efforts aim to further enhance the method's robustness and practical applicability. Additionally, comparative experiments in diverse scenarios will be conducted to validate the effectiveness and applicability of the proposed approach.
KW - Anchor Localization
KW - Real-Time Performance
KW - Sensor Fusion
KW - Time Difference of Arrival (TDOA)
KW - Ultra-Wideband (UWB)
UR - https://www.scopus.com/pages/publications/105032694045
U2 - 10.1109/INDIN64977.2025.11279058
DO - 10.1109/INDIN64977.2025.11279058
M3 - 会议稿件
AN - SCOPUS:105032694045
T3 - IEEE International Conference on Industrial Informatics (INDIN)
BT - 2025 IEEE 23rd International Conference on Industrial Informatics, INDIN 2025
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 23rd International Conference on Industrial Informatics, INDIN 2025
Y2 - 12 July 2025 through 15 July 2025
ER -