Accuracy Analysis and Simulation of Angle of Arrival Estimation in 5G Positioning

Global Navigation Satellite System (GNSS) is susceptible to signal obstruction in complex environments such as indoors or urban canyons, leading to degraded visibility or even complete failure. As an effective supplement, the 5G system, with its full coverage capabilities and advanced technologies, can improve spatial angle resolution and achieve positioning based on uplink (UL) Angle of Arrival (AOA) at the Base Station (BS) side. However, current theoretical analyses of angle estimation accuracy primarily focus on linear arrays, with limited research exploring planar arrays used in practical applications. To explore the UL-AOA estimation and UL-AOA-based UE positioning accuracy using 5G Sounding Reference Signal (SRS), we derive the Cramér-Rao Lower Bound (CRLB) for AOA estimation and AOA positioning using planar arrays, and conduct Monte Carlo simulations on angle estimation algorithms, including the beam search, MUltiple SIgnal Classification (MUSIC), Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT), and improved beam space MUSIC for static User Equipment (UE) or pedestrian handheld terminals under Line-of-Sight (LoS) and Non-Line-of-Sight (NLoS) conditions. The results indicate that super-resolution angle estimation algorithms yield minimized Root Mean Square Error (RMSE), with the difference from the CRLB reduced to within 1°. In urban canyon scenarios, the confidence level of super-resolution algorithms in maintaining the 3D positioning errors within 4m can reach 90%, approaching more closely to the CRLB of AOA positioning. This work provided a reference for future research on high-precision positioning in 5G environments.