GNSS/IMU/LiDAR fusion positioning research

To improve the anti-interference and positioning accuracy of conventional integrated navigation and positioning under the conditions of low-cost satellite receivers and IMU, this paper proposes to fuse GNSS, inertial measurement unit (IMU), and laser radar (LiDAR) to enhance the robustness and accuracy of positioning. In complex environments such as high-rise buildings, where satellite signals are lost, the robustness and accuracy of navigation and positioning can be improved by fusing IMU and GNSS. However, if the satellite signal loss time is too long, the IMU/GNSS integrated positioning accuracy under low-cost conditions is still not ideal. This paper proposes to use the position information output by the LiDAR odometer and the conventional integrated navigation to perform fusion positioning through extended Kalman filter (EKF). The experiments show that in the unobstructed environment, the fusion positioning standard deviation (STD) accuracy is 53.7% higher than the satellite positioning, the root mean square error (RMSE) accuracy is 56% higher, the fusion positioning STD accuracy is 37.9% higher than the GNSS/IMU integrated positioning, and the RMSE accuracy is 38.6% higher. In the obstructed environment, the fusion positioning STD accuracy is 59.4% higher than the satellite positioning, the RMSE accuracy is 71.3% higher, the fusion positioning STD accuracy is 26.3% higher than the GNSS/IMU integrated positioning, and the RMSE accuracy is 33.7% higher.