Performance Analysis of GNSS + 5G Hybrid Positioning Algorithms for Smartphones in Urban Environments

Smartphone positioning methods relying solely on GNSS are susceptible to significant errors in urban environments due to challenging observation conditions. To enhance position accuracy, this paper introduces a novel 5G observation model based on unit vectors and evaluates its performance using several user locations and precision observation data. The results demonstrate that the unit vector method, compared to the traditional angle of departure approach, effectively reduces the nonlinearity of the observation model, leading to a substantial improvement in the 5G system’s positioning accuracy. Furthermore, we conduct experiments to investigate the impact of the geometric distribution of 5G base station height on positioning accuracy. The results reveal a significant influence, highlighting the importance of considering base station height in the positioning process. In the urban environment, introducing 5G base station angle observations as an aid to GNSS significantly enhances the reliability of smartphone positioning, achieving positioning errors of less than one meter. Notably, this approach outperforms the introduction of 5G distance observations, providing valuable insights for the development of seamless indoor and outdoor positioning systems in the future.