Research On Vehicle Navigation Integrity Monitoring Method Based On 5G/GNSS Integration

With the rapid development of autonomous driving technology,intelligent transportation systems have shown advantages such as high efficiency and low traffic accident rates.However,autonomous vehicles still face safety risks in complex road environments.In particular,in dynamic urban environments,the Global Navigation Satellite Systems(GNSS)as the primary outdoor positioning system may experience obstruction from tall buildings and other obstacles,leading to challenges such as reduced positioning accuracy and unreliable positioning results for autonomous driving systems.Therefore,it is important to study the integrity of combined positioning systems in urban environments to improve the safety performance of self-driving vehicles.This study focuses on the integrity performance of self-driving vehicles for autonomous positioning on urban streets.Firstly,5G positioning signals is used as an auxiliary navigation source,and an error model for 5G positioning was established.Then,a 5G/GNSS combination positioning method was studied,and an integrity monitoring method based on the 5G/GNSS was proposed.Finally,a simulation verification platform based on MATLAB was built,and real-world data was collected to verify the monitoring performance of the proposed method.The main research content and innovation points of this paper are as follows:To address the challenges of inadequate characterisation of the auxiliary positioning capability of 5G signals in urban environments and incomplete error models,the positioning capability of 5G signals in multipath propagation environments is evaluated and a multipath error model for 5G positioning is established.Firstly,the correlation of different positioning signals is investigated to analyse the influencing factors that may be associated with multipath errors.Then,the positioning errors of different 5G signals under the multipath propagation channel model were estimated using a delayed loop tracking method.Finally,the standard deviation of the positioning errors under different conditions and the cumulative distribution function(CDF)were statistically calculated,and a complete 5G positioning error model was established.To address the challenge of the current 5G/GNSS combined positioning system’s inability to satisfy the stringent accuracy and reliability requirements of the vehicle navigation system,a solution based on the decomposition separation principle is proposed in this paper.This method employs a combination observation model of satellite pseudorange and 5G round-trip time(RTT),and weights the combined observation quantity using the established 5G positioning error model to optimize the distribution of integrity risk in the decomposition separation plan.Furthermore,the paper derives the Horizontal Protection Level(HPL)calculation method and Fault Detection and Exclusion(FDE)algorithm for the combined navigation system,and updates the fault detection threshold.Finally,the proposed integrity monitoring method based on the decomposition separation principle is validated through simulation,which demonstrates improved positioning accuracy and integrity monitoring performance compared to the existing 5G/GNSS positioning methods.The simulation results indicate that the proposed integrated integrity monitoring method based on decomposition separation principle enhances fault detection probability by 30%compared to traditional GNSS integrity monitoring methods,and reduces HPL by 71.77%.To verify the feasibility of the 5G positioning error model established in this paper and the monitoring performance of the proposed integrity monitoring method,a MATLAB-based vehicle navigation integrity monitoring simulation platform was built,and simulations were performed for autonomous driving scenarios.Finally,real-world data based on GNSS observation data shared by the Hong Kong Polytechnic University team was used to verify the method.The simulation and experimental results for autonomous driving scenarios both showed that the 5G positioning error model and the integrity monitoring method proposed in this paper have significant effects in improving the positioning accuracy and integrity of self-driving systems.