米氏(Mie)散射激光雷达在大气气溶胶和云层的空间分布监测中应用非常广泛, 但对其回波信号进行自动准确的云检测仍存在一定的困难。微分零交叉法是目前应用最多的算法之一, 但是在信噪比较低情况下会造成较多误判。根据激光雷达回波信号的特点, 对微分零交叉法进行了改进。改进的算法中参考了候选点信号强度特性和前后时刻的云层信息, 有效地修正了一些较为明显的误判。最后根据云检测结果对云消光系数和光学厚度进行了反演, 较为客观地反映了云层内部光学参数的变化特性, 初步实现了较为精确的激光雷达自动云检测和参数反演。

Mie lidar is widely used in the spatial distribution detection of atmospheric aerosol and cloud, but there are some difficulties in cloud detection from return signal automatically and accurately. The differential zero-crossing method is one of the dominant methods, but it has a disadvantage of big uncertainty when the signal-to-noise ratio is low. The differential zero-crossing method is improved based on the feature of the return signal of LiDAR. Namely the former and latter cloud information and signal intensity are referred to in the improved method, so obvious errors are efficiently avoided. Finally, the cloud extinction coefficient and optical thickness are retrieved based on the cloud detection result. The variations feature of the optical properties is represented objective. Further more, precise and automatic lidar cloud detection and coefficient retrieval are achieved preliminarily.