Research on Satellite Navigation and Positioning Based on Laser Point Cloud Data

The existing satellite navigation and positioning technology can’t meet the requirement of target positioning accuracy, and the results are not obtained in time. In order to improve the accuracy and real-time of satellite navigation and positioning, a satellite navigation and positioning method based on laser point cloud data is proposed. In order to reduce the influence of interference factors, the mean filter method is used to denoise the laser point cloud data, and the Euclidean threshold region segmentation method is used to segment discrete data points. Aiming at extracting geometric features of objects, corner features of point cloud data are extracted based on geometric features. On the basis of the preprocessing results, the absolute position information, angular velocity and driving speed of satellite navigation are acquired by laser point cloud data, and the navigation datum line and characteristic points in the navigation path are acquired by image processing in machine vision. Satellite navigation and positioning based on laser point cloud data are completed. The simulation results show that the proposed method can effectively improve the positioning accuracy and operation efficiency, and can meet the practical application requirements.