Abstract: Due to coupling interference caused by temperature changes, mechanical vibrations, and electromagnetic interference, the pseudo monitoring data of multispectral light detection and ranging (LiDAR)cannot truly reflect the actual information of the target object, resulting in data distortion. In order to improve the accuracy and reliability of multispectral LiDAR data, it is necessary to correct the pseudo monitoring data of multispectral LiDAR. Firstly, the bias caused by ambient temperature during multispectral LiDAR measurement is eliminated using the mean removal method, and the five point third-order smoothing method is further used to remove the interference noise caused by mechanical vibrations; Then, the trend terms are removed using the least squares method to address the impact of electromagnetic interference on the data, achieving pre-processing of multispectral LiDAR pseudo monitoring data; Finally, based on the known positions of the base stations, the pseudo-range difference method is adopted to correct the multispectral LiDAR pseudo monitoring data. Experimental results show that the proposed method achieves good multispectral LiDAR measurement performances with small displacement frequency monitoring errors, which can effectively improve the accuracy and reliability of the measurement results.