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如何对低云下雾霾的激光雷达探测数据进行准确定标, 一直是米散射激光雷达数据反演中一个有待解决的问题. 对于低云和雾霾同时出现的天气, 激光很难穿透云层, 不能利用大气清洁层对激光雷达信号定标. 而对于探测高度小于6 km的便携式米散射激光雷达, 由于探测高度较低, 也很难利用大气清洁层对激光雷达数据进行定标. 本文根据Fernald前向积分方程的特点, 提出了一种气溶胶消光系数迭代算法. 通过对反演过程进行特定设置, 每经过一次迭代, 利用气溶胶消光系数迭代算法得到的气溶胶消光系数反演值与其真实值之间的差值就会相应减小. 经过几次迭代后, 气溶胶消光系数反演值与真实值之间的差值就会小到可以忽略不计. 初步反演结果表明: 利用气溶胶消光系数迭代算法, 无需对激光雷达探测数据定标就能精确反演出气溶胶消光系数廓线. -
关键词:
- 激光雷达 /
- 雾霾 /
- 气溶胶消光系数 /
- Fernald前向积分方程
How to accurately calibrate the lidar data about haze in the presence of some cloud layers over the haze has always been a subject to be solved for data inversion of Mie scattering lidar. It is difficult for laser to penetrate the haze and clouds simultaneously, so the backscattering signal of lidar cannot be calibrated by using a clear air layer when the haze is under the low clouds. For the portable Mie scattering lidar with a detecting range of less than 6 km, it is also difficult to calibrate the lidar signals by using a clear air layer. An iterative algorithm for aerosol extinction coefficient is proposed based on the characteristics of the Fernald forward integral equation in this paper. By specific settings for the inversion process, the difference between the inversion value and the expected one of aerosol extinction coefficient is reduced after each iteration. After several iterations, the difference between the inversion value and the expected one of aerosol extinction coefficient is small enough to be negligible. The disadvantage of the iterative algorithm for aerosol extinction coefficient is that the inversion results are affected by the overlap factor of lidar. The errors of lidar overlap factor measured experimentally at different times are slightly different. However, the influence about the overlap factor of lidar measured experimentally at different times on the inversion results is slightly different when the iterative algorithm for aerosol extinction coefficient is used to calculate aerosol extinction coefficient. The results of preliminary calculation show that the iterative algorithm of aerosol extinction coefficient can accurately reproduce aerosol extinction coefficient profile without needing calibration of the lidar data. For the haze detection signal that cannot be calibrated by a clear air layer, the vertical distribution of the haze extinction coefficient can be accurately retrieved by the iterative algorithm for aerosol extinction coefficients. The vertical distribution of aerosol extinction coefficients can also be accurately retrieved by using the iterative algorithm of aerosol extinction coefficients for the Mie backscattering lidar data with the measuring height less than 6 km. Through comparative analysis and research, it is found that for the same lidar data, the aerosol extinction coefficient obtained by the iterative algorithm for aerosol extinction coefficient is closer to the actual value than that by the slope method. [1] 孙国栋, 秦来安, 张巳龙, 何枫, 谭逢富, 靖旭, 侯再红 2018 67 054205
Google Scholar
Sun G D, Qin L A, Zhang S L, He F, Tan F F, Jing X, Hou Z H 2018 Acta Phys. Sin. 67 054205
Google Scholar
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Chi R L, Wu D C, Liu B, Zhou J 2009 Spectrosc. Spect. Anal. 29 001468
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Google Scholar
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Google Scholar
[5] 陈莎莎, 徐青山, 徐赤东, 余东升, 陈小威 2017 光学学报 37 9
Chen S S, Xu Q S, Xu C D, Yu D S, Chen X W 2017 Acta Opt. Sin. 37 9
[6] Huang X Y, Yang X W, Geng F H, Zhang H, He Q S, Bu L B 2010 J. Opt. Soc. Korea 14 185
Google Scholar
[7] Hee W S, Khor W Y, Lim H S, Jafri M Z M 2015 AIP Conference Proceedings Kuala Lumpur, November 18–19, 2014 040015
[8] Liang M, Peng G, Yang Y, Zheng K 2017 Opt. Express 25 A628
Google Scholar
[9] Klett J D 1981 Appl. Opt. 20 211
Google Scholar
[10] Russell P B, Swissler T J, Mccormick M P 1979 Appl. Opt. 8 3873
[11] Chiang C W, Das S K, Nee J B 2008 J. Quant. Spectrosc. Radiat. Transfer 109 1187
Google Scholar
[12] NOAA U, Force U A 1976 US Standard Atmosphere
[13] Liu H T, Wang Z Z, Zhao J X, Ma J J 2018 Curr. Opt. Photon. 2 119
[14] Salem E 2007 J. Mod. Opt. 42 1439
[15] 刘厚通, 陈良富, 苏林 2011 60 064204
Google Scholar
Liu H T, Chen L F, Su L 2011 Acta Phys. Sin. 60 064204
Google Scholar
[16] Fernald F G 1984 Appl. Opt. 23 652
Google Scholar
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[20] 狄慧鸽, 华灯鑫, 王玉峰, 闫庆 2013 62 094215
Di H G, Hua D X, Wang Y F, Yan Q 2013 Acta Phys. Sin. 62 094215
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图 2 大气透过率初始值与第一次迭代值之间的关系
Fig. 2. The relationship between the initial values and the first iterative values of atmospheric transmittance.
图 3 利用气溶胶消光系数迭代算法反演得到的气溶胶消光系数廓线
Fig. 3. The aerosol extinction coefficient profiles retrieved by the iterative algorithm of aerosol extinction coefficient.
图 4 米散射激光雷达距离校正信号
Fig. 4. The range corrected lidar signal of the Mie scattering lidar.
图 5 利用气溶胶消光系数迭代算法与其他定标方法获得的气溶胶消光系数比较
Fig. 5. Comparison of aerosol extinction coefficients obtained by the iterative algorithm of aerosol extinction coefficient and other calibration methods.
图 7 不同的激光雷达几何重叠因子误差所对应的激光雷达距离校正信号
Fig. 7. The range corrected lidar signals corresponding to different errors of lidar geometric overlap function.
图 8 几何重叠因子误差对气溶胶消光系数反演值的影响
Fig. 8. The influence of lidar overlap function error on the retrievals of aerosol extinction coefficients.
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[1] 孙国栋, 秦来安, 张巳龙, 何枫, 谭逢富, 靖旭, 侯再红 2018 67 054205
Google Scholar
Sun G D, Qin L A, Zhang S L, He F, Tan F F, Jing X, Hou Z H 2018 Acta Phys. Sin. 67 054205
Google Scholar
[2] 迟如利, 吴德成, 刘博, 周军 2009 光谱学与光谱分析 29 001468
Chi R L, Wu D C, Liu B, Zhou J 2009 Spectrosc. Spect. Anal. 29 001468
[3] Lefrere J, Pelon J, Cahen C, Hauchecorne A, Flamant P 1981 Appl. Opt. 20 A70
Google Scholar
[4] Ansmann A, Wandinger U, Riebesell M, Weitkamp C, Michaelis W 1992 Appl. Opt. 31 7113
Google Scholar
[5] 陈莎莎, 徐青山, 徐赤东, 余东升, 陈小威 2017 光学学报 37 9
Chen S S, Xu Q S, Xu C D, Yu D S, Chen X W 2017 Acta Opt. Sin. 37 9
[6] Huang X Y, Yang X W, Geng F H, Zhang H, He Q S, Bu L B 2010 J. Opt. Soc. Korea 14 185
Google Scholar
[7] Hee W S, Khor W Y, Lim H S, Jafri M Z M 2015 AIP Conference Proceedings Kuala Lumpur, November 18–19, 2014 040015
[8] Liang M, Peng G, Yang Y, Zheng K 2017 Opt. Express 25 A628
Google Scholar
[9] Klett J D 1981 Appl. Opt. 20 211
Google Scholar
[10] Russell P B, Swissler T J, Mccormick M P 1979 Appl. Opt. 8 3873
[11] Chiang C W, Das S K, Nee J B 2008 J. Quant. Spectrosc. Radiat. Transfer 109 1187
Google Scholar
[12] NOAA U, Force U A 1976 US Standard Atmosphere
[13] Liu H T, Wang Z Z, Zhao J X, Ma J J 2018 Curr. Opt. Photon. 2 119
[14] Salem E 2007 J. Mod. Opt. 42 1439
[15] 刘厚通, 陈良富, 苏林 2011 60 064204
Google Scholar
Liu H T, Chen L F, Su L 2011 Acta Phys. Sin. 60 064204
Google Scholar
[16] Fernald F G 1984 Appl. Opt. 23 652
Google Scholar
[17] Xian J H, Han Y L, Huang S Y, Sun D S, Zheng J, Han F, Zhou A R, Yang S C, Xu W J, Song Q C, Wei L F, Tan Q Z, Li X Z 2018 Opt. Express 26 34853
Google Scholar
[18] Wong M S, Qin K, Lian H, Campbell J R, Lee K H, Sheng S J 2017 Atmos. Environ. 154 189
Google Scholar
[19] Wang J, Zhang T, Liu W, Liu J, Wan X 2018 OSA Technical Digest (Optical Society of America, 2018) Singapore November 5–8, 2018 ET3A.1.
[20] 狄慧鸽, 华灯鑫, 王玉峰, 闫庆 2013 62 094215
Di H G, Hua D X, Wang Y F, Yan Q 2013 Acta Phys. Sin. 62 094215
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