个人信息Personal Information
副教授
博士生导师
硕士生导师
性别:男
毕业院校:大连理工大学
学位:博士
所在单位:光电工程与仪器科学学院
电子邮箱:gongzf@dlut.edu.cn
Adaptive digital filter for the processing of atmospheric lidar signals measured by imaging lidar techniques
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论文类型:期刊论文
发表时间:2021-01-10
发表刊物:APPLIED OPTICS
卷号:59
期号:30
页面范围:9454-9463
ISSN号:1559-128X
摘要:The lidar signal measured by the atmospheric imaging lidar technique is subject to sunlight background noise, dark current noise, and fixed pattern noise (FPN) of the image sensor, etc., which presents quite different characteristics compared to the lidar signal measured by the pulsed lidar technique based on the time-of-flight principle. Enhancing the signal-to-noise ratio (SNR) of the measured lidar signal is of great importance for improving the performance of imaging lidar techniques. By carefully investigating the signal and noise characteristics of the lidar signal measured by a Scheimpflug lidar (SLidar) based on the Scheimpflug imaging principle, we have demonstrated an adaptive digital filter based on the Savitzky-Golay (S-G) filter and the Fourier analysis. The window length of the polynomial of the S-G filter is automatically optimized by iteratively examining the Fourier domain frequency characteristics of the residual signal between the filtered lidar signal and the raw lidar signal. The performance of the adaptive digital filter has been carefully investigated for lidar signals measured by a SLidar system under various atmospheric conditions. It has been found that the optimal window length for near horizontal measurements is concentrated in the region of 90-150, while it varies mainly in the region of 40-100 for slant measurements due to the frequent presence of the peak echoes from clouds, aerosol layers, etc. The promising result has demonstrated great potential for utilizing the proposed adaptive digital filter for the lidar signal processing of imaging lidar techniques in the future. (C) 2020 Optical Society of America