Evaluation on Low-cost GNSS/IMU/Vision Integration System in GNSS-denied Environments

Currently, the Global Navigation Satellite System (GNSS) measurements-based Real-Time Kinematic (RTK) and Precise Point Positioning (PPP) technologies are the two effective methods to provide users with centimeter-level positioning solutions in strong satellite observability environments. However, the performance (precision, continuity, and reliability) would seriously degrade while suffering challenging environments. To improve GNSS performance around the signals blocked areas, the Inertial Navigation System (INS) and vision camera sensors are integrated with GNSS in this contribution. Firstly, we design a GNSS position/INS/Vision integration based on Multi-State Constraint Kalman Filter (MSCKF). Then, a set of vehicle-borne data collected under GNSS-denied environments are processed and analyzed to assess the performance of such presented algorithm. Results illustrate that (1) In GNSS-denied environments, solutions calculated by both PPP and RTK are un-continuous; (2) however, its performance can be improved while using multi-GNSS observations; (3) with the aids from INS and vision, GNSS performance in terms of accuracy, continuity, and availability can be upgraded significantly even suffering satellite signal outages.