Research on High-Precision Indoor Positioning Methods for High-Speed Railway Depots Based on UWB and Laser Radar

A single sensor often cannot simultaneously achieve high accuracy, strong anti-interference capability, and rich data information during positioning, making it difficult to meet the sub-metre to centimetre-level positioning requirements of high-speed rail maintenance operations. Therefore, this paper proposes a feature-level fusion positioning method based on ultra-wideband (UWB) and Light Detection and Ranging (LiDAR). This method first uses spatio-temporal calibration technology to unify the spatio-temporal reference frames of UWB and LiDAR. It then utilises the target identity information and coarse position provided by UWB to construct a dynamic three-dimensional gated region, effectively constraining the search range of the LiDAR point cloud and reducing computational complexity. Finally, it extracts high-precision point cloud features from the LiDAR within the gated region and combines them with the global position estimation from UWB to achieve precise target position output. Experimental results show that the maximum error of this fusion positioning method does not exceed 10 cm, with a minimum error of 3.16 cm. It effectively combines UWB’s identity recognition and global position estimation capabilities with LiDAR’s local high-precision positioning advantages, meeting the high-precision positioning requirements of indoor operational scenarios.