Mie scattering lidar is a remote sensing instrument with a high spatial and temporal resolution, and it has received extensive attention in research since it has successfully been applied in the fields such as atmospheric aerosol observation, cloud and fog characteristic analysis, and pollution emission monitoring. However, most of these ground-based lidars belong to the monostatic structure with the same transmitting and receiving sites. While they are been utilized to detect tropospheric or boundary layer, the transmitting and receiving coaxial systems (limited by the reflective telescope structure) or the transmitting and receiving systems with different axes (also known as off-axis) are almost affected by the near-field blind area and overlap factor, which results in the loss of near-field signals of the lidar or the reduction of accuracy. Therefore, the data of near-field point-type probing instruments (such as horizontal visibility meter, PM2.5 meter, and particle spectrometer) are usually required for data correction, compensation, or verification in these applications of lidar. However, the near-field atmospheric characteristics are usually essential data in meteorological, environmental, and other fields, which greatly limits the engineering and application process of the lidar. Therefore, overlap factor correction of lidar near-field signals and blind area have always restricted the practical process of lidar.

Based on the assumption of horizontal atmosphere uniformity, a multi-angle scanning near-field signal adaptive correction method for lidar is proposed using the vertical scanning function of the developed two-dimensional scanning lidar system. Firstly, according to the overlap factor model of an off-axis lidar system, the influence of laser beam divergence angle, telescope field angle, optical axis distance, and optical axis angle on the overlap factor is analyzed. Secondly, using the Fernald aerosol retrieval algorithm and taking the advantage of lidar vertical scanning, a multi-elevation angle correction scheme dependent on signal-to-noise (SNR) threshold is proposed to achieve adaptive scanning control of different atmospheric states. Combined with the ground extinction coefficient retrieved by the Collis method and the multi-angle scanning remote sensing data, the aerosol extinction coefficient without a blind area profile is retrieved, and the effectiveness of the correction scheme under different weather conditions is compared.

Based on the stratification assumption of a uniform atmosphere, the multi-elevation angle scanning control and correction steps (Figs. 5 and 6) are designed to realize the adaptive scanning control for different atmospheric states. Using multi-angle scanning remote sensing data and taking the result of Collis retrieval by horizontal detection as the ground extinction coefficient, the blind area profile of the atmospheric aerosol extinction coefficient is obtained [Fig. 7 (c) and Fig. 8 (c)]. When the horizontal visibility is better than 18 km and the SNR threshold is 20, the average relative deviation of the overlap factor correction curve and the correction curve of the horizontal detection method is about 20% [Fig. 7 (d) and Fig. 8 (d)], and the average relative error of the overlap factor curve is 4.2% (Fig. 9). Finally, a group of data with 24-h observation is shown to verify the scanning correction method (Fig. 10), and the retrieval without blind area of atmospheric aerosol can be realized.

In order to correct the near-field aerosol extinction profile of ground-based Mie scattering lidar, a vertical scanning correction method and multi-angle retrieval algorithm are proposed for near-field signals of Mie scattering lidar, and then the adaptive control of the atmospheric state is probed based on the assumption of horizontal atmosphere uniformity. Owing to the scattering lidar equation, a model of the overlap factor and blind area in the near field of the lidar is constructed, and the characteristics of the overlap factor and the blind area are analyzed and simulated based on the developed two-dimensional scanning lidar. In combination with the Fernald retrieval algorithm, a multi-elevation scanning control and correction scheme dependent on SNR is presented to realize adaptive scanning control for different atmospheric conditions. The profile of atmospheric aerosol extinction coefficient without blind area under different weather conditions is obtained by merging multi-angle scanning remote sensing data and the ground extinction coefficient obtained by the Collis method of horizontal detection, and the effectiveness of this scheme is verified. The data analysis results show that the adaptive correction of the lidar overlap factor can be achieved through seven elevations of about 15-min observation with the SNR ratio of 20 as the threshold when the horizontal visibility is better than 18 km. The mean relative deviation of the obtained calibration curve from horizontal correction is about 20%, and the mean relative error of the correction results of the overlap factor curves is 4.2%, which can realize the retrieval of atmospheric aerosol without blind area.