Time-of-Arrival Estimation in Challenging Environments Using Commercial 5G NR Signals for Outdoor Positioning

The proliferation of 5G Internet of Things (IoT) devices in daily life has significantly increased the demand for 5G-based positioning services. This article presents a methodology for accurate time-of-arrival (TOA) estimation of commercial 5G new radio (NR) signals, specifically addressing the severe interference commonly encountered in challenging environments. To mitigate high noise levels, we first apply a raised cosine filter for initial denoising of channel state information (CSI), followed by frequency-domain averaging and normalization to further suppress residual noise. For precise TOA estimation, we develop an algorithm that leverages a delay lock loop (DLL) for robust signal tracking, enhanced by initialization and relocking mechanisms supported by space-alternating generalized expectation-maximization (SAGE). Additionally, we adapt several classic global positioning system (GPS) delay discriminators for compatibility with 5G NR signals, aiming to identify DLLs that perform effectively under adverse conditions. Comprehensive validation through simulations and field tests demonstrates the proposed system’s robustness and practical applicability. Furthermore, we identify delay discriminators that are particularly well-suited for deployment in challenging environments.