Autonomous Ground Vehicle Navigation with GNSS/5G Integration

In this paper, we introduce a novel integrated navigation system that merges the capabilities of the global navigation satellite systems (GNSS) and fifth-generation (5G) wireless technology to deliver precise location-based services. Our approach entails the development of an integrated navigation framework adept at addressing nonlinear implicit constraints and multipath environments, resulting in a highly resilient and accurate navigation solution. The framework concurrently assesses the vehicle's position, velocity, and acceleration states, alongside determining the disparity between the dynamic stochastic clock error states (bias and drift) of the vehicle-mounted receiver and the generation Node B (gNB) clock. Within this framework, we propose a practical adaptive iterative extend Kalman filter (AIEKF) method that efficiently manages nonlinear implicit constraints and multipath propagation within a 5G environment. Simulation outcomes demonstrate the superiority of our AIEKF method over the traditional IEKF method, particularly in handling 5G multipath scenarios. Our results underscore that the proposed GNSS/5G method markedly enhances navigation accuracy in both urban junctions and highway scenarios, showcasing a 61.71% and 47.51% reduction in RMSE, respectively, compared to the 5G-only navigation solution.