TY - JOUR
T1 - 改进简单多尺度法的激光雷达云检测
AU - Chen, Siying
AU - Wang, Jiaqi
AU - Chen, He
AU - Zhang, Yinchao
AU - Guo, Pan
AU - Nian, Xuan
AU - Sun, Zhuoran
AU - Chen, Su
N1 - Publisher Copyright:
© 2020, Editorial Board of Journal of Infrared and Laser Engineering. All right reserved.
PY - 2020/11/25
Y1 - 2020/11/25
N2 - As one of the important means of active remote sensing of atmosphere, lidar is widely used in aerosol and cloud detection. Based on the simple multiscale algorithm for layer detection, a cloud detection algorithm was proposed that could improve the accuracy of the cloud -base height when the SNR was greater than 5 by adding the threshold of the number of scales. By simulating the echo signal of multi-peak inside the cloud, the algorithm obtained the threshold range of the optimization scale. At the same time, by adding feature segment merge, the disadvantage of the simple multiscale method, missing the single -layer with multipeak, could be improved. The effective 532 nm Mie lidar data was processed which had more than 75 min detection time and stable structure from May to July 2019 by using differential zero-crossing method, simple multiscale method and improved algorithm were proposed respectively, and based on the cloud-base height of differential zero-crossing method, the average error of the mean square root obtained by the improved algorithm decreased by 32.65%, the uncertainty average decreased by 33.80%. Then the effectiveness of the improved algorithm in improving the accuracy of the cloud-base height is proved.
AB - As one of the important means of active remote sensing of atmosphere, lidar is widely used in aerosol and cloud detection. Based on the simple multiscale algorithm for layer detection, a cloud detection algorithm was proposed that could improve the accuracy of the cloud -base height when the SNR was greater than 5 by adding the threshold of the number of scales. By simulating the echo signal of multi-peak inside the cloud, the algorithm obtained the threshold range of the optimization scale. At the same time, by adding feature segment merge, the disadvantage of the simple multiscale method, missing the single -layer with multipeak, could be improved. The effective 532 nm Mie lidar data was processed which had more than 75 min detection time and stable structure from May to July 2019 by using differential zero-crossing method, simple multiscale method and improved algorithm were proposed respectively, and based on the cloud-base height of differential zero-crossing method, the average error of the mean square root obtained by the improved algorithm decreased by 32.65%, the uncertainty average decreased by 33.80%. Then the effectiveness of the improved algorithm in improving the accuracy of the cloud-base height is proved.
KW - Cloud detection
KW - Cloud-base height
KW - Lidar
KW - Simple multiscale algorithm
UR - http://www.scopus.com/inward/record.url?scp=85099035136&partnerID=8YFLogxK
U2 - 10.3788/IRLA20200379
DO - 10.3788/IRLA20200379
M3 - 文章
AN - SCOPUS:85099035136
SN - 1007-2276
VL - 49
JO - Hongwai yu Jiguang Gongcheng/Infrared and Laser Engineering
JF - Hongwai yu Jiguang Gongcheng/Infrared and Laser Engineering
M1 - 20200379
ER -