摘要
利用梯度法对激光雷达信号进行处理,检测出突变部分的幅度和位置,根据梯度信息计算相应的平移序列,加入到原始信号中,使所得信号中不包含突变信息。利用经验模态分解(EMD)方法对去突变信号进行分解和去噪就可以避免模态混叠和突变位置附近出现的局部振荡现象。将该方法应用于实际激光雷达数据去噪过程中,实验结果表明,该方法能消除由突变引起的重构信号局部振荡现象,对信号平稳部分的噪声能有效地滤除,又能较好地保留信号的突变信息。
A grads method is used to process lidar signal, by which the scopes and positions of abrupt change can be detected. Based on these grads messages, a translation sequence can be calculated and is added to original lidar signal, which makes the parts of abrupt change in original lidar signal removed. The abrupt change removed signal is decomposed and denoised by empirical mode decomposition, which can avoid mode mix and local surge phenomena. This denoising method is applied to real lidar data denoising. The experiment results show the effectiveness of this method. It can remove noise in signal effectively in flat part and keep abrupt change well in signal.
出处
《光学学报》
EI
CAS
CSCD
北大核心
2011年第12期71-75,共5页
Acta Optica Sinica
基金
国家自然科学基金(60677041)资助课题
关键词
信号处理
激光雷达
经验模态分解
梯度检测
信号去噪
signal processing lidar empirical mode decomposition grads detecting signal denoising
