Iterative maximum-likelihood estimation algorithm for clock offset and skew correction in UWB systems assisted by 5G NR multipath

• Published in: Measurement : journal of the International Measurement Confederation Vol. 242; p. 115823
• Main Authors: Hu, Qingsong, Wang, Liudi, Luo, Yujia, Cheng, Yuanxun, Kou, Zhihao, Xie, Zhiwei
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.01.2025
• Subjects: 5th-Generation New radio; Clock offset and clock skew; Iterative maximum likelihood estimation; Positioning error; Ultra-wideband; Ultra-wideband; Clock offset and clock skew; 5th-Generation New radio; Positioning error; Iterative maximum likelihood estimation
• ISSN: 0263-2241
• DOI: 10.1016/j.measurement.2024.115823

•We analyze the impact of clock offset and clock skew on timing error in UWB system.•A framework is proposed for calibrating timing errors in UWB through Timing Error Group (TEG) identifiers of 5G New Radio (5G NR).•An error estimation algorithm proposed can utilize the multipath of 5G NR to perform nonlinear iterative Maximum Likelihood Estimation (MLE), correcting timing errors in UWB.•The proposed algorithm has been comprehensively simulated to verify its performance and analyze the impact of various factors, demonstrating the new model’s superior positioning accuracy. High-precision location services such as unmanned driving, indoor navigation, and mine positioning have been benefiting significantly with the breakthroughs in Fifth-Generation (5G) technology. This paper proposes a collaborative Time of Flight (TOF) measurement framework for 5G New Radio (NR) in Release 17 and Ultra-Wideband (UWB). The method proposed improves the positioning accuracy by tackling the issues of UWB clock offset and clock skew. To this end, we have designed an innovative correction algorithm that effectively utilizes 5G multipath measurement and Timing Error Group (TEG) identifiers. The algorithm employs a low-complexity iterative maximum likelihood estimation (MLE) method to accurately estimate error parameters and calibrate UWB TOF measurement results. Simulation results show that this algorithm significantly enhances positioning precision and robustness. It reduces positioning error by 24 % and 35 % compared to the baseline algorithm in two representative scenarios. These improvements make it suitable for UWB systems in real-time and complex environments.