New method of lidar ceilometer backscatter signal processing based on Hilbert-Huang transform

被引：0

作者：

He, Junfeng ^{[1
,2
]}

Liu, Wenqing ^{[1
]}

Zhang, Yujun ^{[1
]}

Duan, Lianfei ^{[2
]}

Yang, Luyi ^{[2
]}

Ruan, Jun ^{[1
]}

机构：

[1] Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China

[2] Artillery Academy of PLA, Hefei 230031, China

来源：

Hongwai yu Jiguang Gongcheng/Infrared and Laser Engineering | 2012年 / 41卷 / 02期

关键词：

Backscattering - Optical radar - Information filtering - Meteorological instruments - Feature extraction - Extraction;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

According to backscatter signal characteristics of lidar ceilometer, a backscatter signal feature extraction method was presented based on the Hilbert-Huang Transform (HHT). It worked effectively for HHT's nonlinear and nonstationary signal processing capabilities. The preliminarily denoised signal term and signal trend term were reconstructed respectively from the original backscatter signal, the combination of both was achieved, and brand new backscatter signal was generated after feature extraction. Large number of experimental data analysis shows that the feature extraction method takes advantage of the EMD decomposition and reconstruction filtering, and discards the disadvantage of reducing useful information and ignoring details form backscatter signal. It is well suited for lidar ceilometer backscatter signal processing. With a simple inversion method of backscatter parameters, the method can effectively improve the cloud height and vertical visibility recognition accuracy of the inversion, and can reduce the false positive and false negative rate of cloud height.

引用

页码：397 / 403