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As the effective supplements to Lband radiosonde, both the Doppler wind lidar and wind profiling radar can provide atmospheric wind field information with high spatial and temporal resolution. However, due to the obvious differences between Doppler wind lidar and wind profiling radar in terms of working principles and applicable conditions, the two wind measuring instruments have their own advantages and disadvantages in detection performance, and the detection data of a single instrument can no longer satisfy the requirements of refined forecasting. In this study, Lband radiosonde data from the Nanjiao observation site in Beijing from January to May 2020 are used to evaluate the observational data quality of the Doppler wind lidar and wind profiling radar at the same site. The results show that the Doppler wind lidar has a high consistency with the Lband radiosonde. The correlation coefficients of U and V components of Doppler wind lidar and Lband radiosonde are 0.97 and 0.98, respectively, and the root mean square errors of U and V components of Doppler wind lidar and Lband radiosonde are 1.1 and 0.95 m·s-1, respectively. However, when the detection height is above 2 km, the data acquisition rate of Doppler wind lidar is low and the deviation is large. Compared to Doppler wind lidar, the consistency between the wind profiling radar and Lband radiosonde is slightly worse. The correlation coefficients of U and V components between the wind profiling radar and Lband radiosonde are 0.94 and 0.93, respectively, and the root mean square errors of U and V components between the wind profiling radar and Lband radiosonde are 2.94 and 2.91 m·s-1, respectively. Compared to Doppler wind lidar, wind profiling radar has a longer detection range but a lower temporal resolution, in addition to a larger measurement bias below 0.5 km and above 6 km. Considering the advantages and disadvantages of the doppler wind lidar and wind profiling radar at different detection heights, the horizontal wind measurements from the two wind measuring instruments are first spliced and fused, and then the segmented surface fitting method is used to correct the outliers and compensate for the missing values of the fused wind profiles. Two cases are selected to validate and analyse the effect of fusion. The results show that the consistency between the wind direction and wind speed of the fused wind profile and the Lband radiosonde is significantly improved compared to the measurements of the individual devices before the fusion process.