Laser remote sensing is of great significance for studying aerosol and cloud microphysical properties, radiation forcing effects, and pollutant transport by obtaining vertical distributions of aerosols and clouds. In practical applications, lidar is affected by laser energy, divergence angle and transmittance, which will lead to inconsistent detection data of each radar against the same target. With the gradual scaling-up and normalization of ground-based atmospheric detection lidars, the study of network observation consistency is of great significance. Based on the self-calibration of the lidar system, the solar photometer and atmospheric molecular model are used to ensure that the echo signal of each laser radar is comparable. Through the detection target consistency comparsion test by the laser radar network observation, the consistency accuracy of the radar system detection is verified. The results show that: after calibration, the relative deviation of range corrected signal in 532 nm channel is reduced from 64.89% to 22.16% in height range of 1~2 km, from 49.26% to 8.90% in height range of 2~5 km, and from 46.83% to 10.91% in height range of 9.5~11.5 km. The relative deviation of depolarization ratio in 532 nm is reduced from 69.68% to 20.68% in height range of 1~2 km, from 71.24% to 6.69% in height range of 2~5 km, and from 140.24% to 9.02% in height range of 9.5~11.5 km. The relative deviation of backscattering coefficient in 532 nm is reduced from 37.45% to 23.63% in height range of 1~2 km, from 29.15% to 21.45% in height range of 2~5 km, and from 76.02% to 24.16% in height range of 9.5~11.5 km. The networked lidar have good consistency, and can play an important role in the fields of multi-site high-precision detection, climate change research, carbon emission monitoring, and environmental research, which can provide high-quality and effective data for the study of large-scale atmospheric changes.