A Pseudolite-Aided Navigation and Positioning Method for Complex Terrain Environments

To address the challenges of degraded positioning accuracy, drift, or complete failure in environments where satellite signals are obstructed (e.g., basements, tunnels, canyons, forests, mountainous regions, and urban high-rise buildings), this paper proposes a navigation and positioning algorithm for complex terrains by integrating pseudolites with Time Difference of Arrival (TDOA) and trilateration techniques. First, to enhance the anti-interference capability and positioning accuracy of low-cost satellite receivers in conventional integrated navigation systems, we improve robustness and precision through the fusion of Global Navigation Satellite System (GNSS) and Inertial Measurement Unit (IMU) data. At the front-end processing stage, the algorithm calculates the relative positions and time differences between multiple pseudolites and receivers while integrating absolute position data derived from trilateration for state estimation, thereby providing accurate initial pose initialization for the back-end module. Subsequently, the back-end employs an Extended Kalman Filter (EKF) to fuse data from wheel odometry, GNSS, and IMU, optimizing the algorithm's accuracy and global consistency. Finally, the proposed algorithm is validated in high-dynamic motion scenarios and a comprehensive campus environment. Experimental results demonstrate that, compared to mainstream GNSS/IMU fusion methods and LiDAR-based Simultaneous Localization and Mapping (SLAM) algorithms, the proposed algorithm achieves superior positioning accuracy (with a root mean square error reduction of 58–72% in occluded scenarios) and exhibits enhanced robustness in aggressive motion conditions.