Abstract: Given the current situation where laser ranging data processing algorithms from domestic and international organizations are not publicly available, in this paper an LLR data processing model was established first. Using self-developed software, which implements error algorithms for general relativity effects, atmospheric delay effects, Earth tides, and lunar tides, high-precision LLR data processing was achieved. The results indicate that when using the data processing program to validate the LLR standard point data published by the International Lunar Ranging Service (ILRS) for the years 2006 to 2021, the root mean square residual is approximately 3.7 cm. Thereinto, the root mean square residual of LLR data in 2014 and before is approximately 3cm, and the root mean square residual of LLR data after 2014 is approximately 4cm. Furthermore, to address the issue of reduced accuracy in LLR data validation due to discrepancies between lunar retroreflector coordinates and lunar ephemerides, the least squares method was employed to estimate the coordinates of the lunar retroreflectors. The results show that, when used as input for the program, the adjusted retroreflector coordinates improve the validation accuracy by approximately 0.5 cm.