【摘要】 针对激光雷达系统的近场探测问题，在考虑多影响因素的情况下，提出重叠因子的归一化光学成像模型，以实现重叠因子的高精度校正。基于光学成像原理构建激光雷达重叠因子归一化模型，分析光束准直系数、收发模块半径比、收发模块视场比、收发模块间距半径比、光束能量因子和中央遮挡比等因素对重叠因子的影响规律。当光束能量因子变化时，重叠因子曲线有一个共同交点（340 m,0.454），但该交点会随激光发射光轴的偏离角变化而变化，可作为收发光轴平行度评估的指标。将该模型用于自研的森林火灾预警激光雷达，采用水平实验法验证其有效性。结果表明，当光束能量因子为0.952时，由该模型计算的理论重叠因子与实验法反演结果相比，过渡区内的平均误差控制在0.025以内，校正后的有效探测范围由560 m降低至223 m（盲区边界）。该归一化光学模型有助于分析不同光束能量因子下的系统重叠因子，可推进激光雷达的实用化进程。更多还原

【Abstract】 Objective Lidar is an active remote sensing instrument that detects information such as the distance and physical properties of targets by emitting laser beams and receiving their reflected or backscattered echo signals. It has achieved rapid development and wide application in the field of atmospheric environment detection. Factors such as the structural relationship between the transmitting and receiving modules, the laser speckle effect, and the detector’s receiver efficiency all affect the target signal’s receiving efficiency. The signal loss in the near field, caused by factors like laser beam divergence, telescope field of view, and the axial spacing between modules, is quantified by the overlap factor. This factor represents the signal receiving efficiency at a given detection range. For the near-field detection problem of the lidar system, a normalized optical imaging model of the overlap factor is proposed. The model’s greatest advantage lies in its comprehensive consideration of influencing factors, wide applicability, and high-precision overlap factor correction.Methods This research investigates the normalized optical imaging model for the lidar overlap factor. First, from the perspective of energy loss, the overlap factor can be defined as the ratio of the energy received by the detector to the energy of the echo signal at the transmission distance. Second, based on optical imaging principles, an overlap factor model for lidar is established by considering the laser beam energy distribution, field overlap, central obstruction, and detector reception. Based on the idea of parameter normalization, the 6-dimensional component parameters of the optical model are reduced to a 5-dimensional structural parameter model. Furthermore, by incorporating the laser beam energy factor, a comprehensive 6-dimensional structural parameter model is obtained. Finally, this model is used in the self-developed forest fire early warning lidar, and its validity is verified by the horizontal experimental method.Results and Discussions To address the near-field detection problem in lidar, we propose a normalized optical imaging model for the overlap factor that incorporates six parameters. The influence of these parameters on the overlap factor is analyzed(Fig. 4). The beam energy factor, defined by the difference between uniform and Gaussian distributions, leads to a key characteristic: overlap factor curves corresponding to different normalized parameter sets intersect at a common point [Fig. 4(e)]. The position of this intersection point varies with the deviation angle of the laser emission axis(Fig. 6). Based on this common intersection point, a method for correcting system parallelism is proposed. Furthermore, the model is applied to a self-developed forest-fire early-warning lidar, and its correction validity is verified through horizontal experiments(Fig. 7). The model is used to calculate theoretical overlap factor curves, which are then compared with curves derived from three sets of horizontal experimental data. The results show that the model calculations agree well with the experimental results. Multi-angle, multi-temporal atmospheric aerosol extinction profiles are inverted using the Klett method to verify the effectiveness of the normalized optical imaging model for near-field signal correction(Fig. 8).Conclusions Based on the normalized optical imaging model, the effects of key factors—including the beam collimation coefficient, transceiver module radius ratio, field ratio, axial distance ratio, beam energy factor, and central obstruction ratio—on the overlap factor are analyzed.The analysis shows that, using normalized parameter metrics, the overlap factor curves for different beam energy factors intersect at a value of 0.454 for a detection distance of 340 m. The position of this intersection point varies with the deviation angle of the laser emission axis. This point can be used as an indicator to judge the parallelism of the receiving and transmitting optical axes. This model is used in the self-developed forest-fire early-warning lidar, and the validity of the model correction is verified by the horizontal experimental method when the beam energy factor is 0.95. The average error of the overlap factor in the transition zone is less than 0.025. Multi-angle, multi-temporal atmospheric aerosol extinction profiles are inverted using the Klett method. The results show that after correction with the overlap factor, the effective near-field detection range is reduced from 560 m to 223 m at the end of the blind zone. Therefore, this model demonstrates substantial theoretical and practical value, effectively advancing the engineering maturation of lidar technology.更多还原