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激光雷达进行大气能见度探测时,当探测路径上存在云、雾、烟尘或硬目标时,大气消光系数会在局部发生显著变化,表现为激光雷达回波信号在原有衰减趋势上出现突变。受此影响,直接使用现有算法将导致能见度反演精度低或错误反演。为此提出一种将突变点定位、消光系数边界值确定、消光系数迭代反演相结合的能见度反演算法。首先查找、定位突变信号所在位置;然后剔除突变点,利用斜率法得到消光系数边界值;最后基于Fernald法,以迭代方式反演大气消光系数及能见度。对两种典型大气消光模式的仿真实验表明,该算法提高了能见度反演精度,能够获得更为准确的全局能见度。利用自行研制的激光雷达能见度仪实测回波数据也验证了该算法的有效性。
When Lidar detects atmospheric visibility, the atmospheric extinction coefficient will change significantly locally when there is cloud, fog, soot or hard target in the detection path, which shows that the Lidar echo signal changes abruptly in the original decay trend. Affected by this, direct use of existing algorithms will result in low accuracy or wrong inversion of visibility inversion. Therefore, a method of visibility inversion based on the combination of locating mutation point, determining the boundary value of extinction coefficient and iterative inversion of extinction coefficient is proposed. Firstly, the location of the mutation signal is located and located; then the mutation point is eliminated, and the boundary value of the extinction coefficient is obtained by using the slope method. Finally, the atmospheric extinction coefficient and visibility are iteratively retrieved based on the Fernald method. The simulation experiments of two typical atmospheric extinction patterns show that the proposed algorithm can improve the accuracy of visibility inversion and obtain more accurate global visibility. The validity of this algorithm is also verified by the measured echo data measured by a laser radar viscometer.