Feature-Aided RTK/LiDAR/INS Integrated Positioning System with Parallel Filters in the Ambiguity-Position-Joint Domain for Urban Environments

As the modern navigation business evolves, demands for high-precision positioning in GNSS-challenged environments increase, and integrated system composed of Global Navigation Satellite System (GNSS)-based Real-Time Kinematic (RTK), inertial (INS), Light Detection Ranging (LiDAR), etc., is accepted as most feasible solution to issue. For prior-map-free situations, only sensor with a global frame, RTK determines maintains precision system. However, performance degrades greatly environments, existing systems adopt loose coupling mode, which does nothing improve and, thus, prevents from further improvement. Aiming at improving RTK/LiDAR/INS system, we proposed an innovative algorithm that utilizes register LiDAR features while integrating pre-registered adopts parallel filters ambiguity-position-joint domain weaken effects low satellite availability, cycle slips, multipath. By doing so, can fix rate stability environments. The results theoretical analyses, simulation experiments, road test proved method improved guaranteed whole