基于希尔伯特-黄变换（HHT）和Savitzky-Golay滤波，提出了一种结合HHT时频分析的半导体激光云高仪后向散射信号去噪方法。该方法在对云高仪后向散射信号的噪声特性及传统去噪方法的缺陷进行研究的基础上，选择截止分量阶一定的自适应时变时空滤波器组（TFB）结构并辅助Savitzky-Golay滤波抑制噪声，最后利用HHT时频分析辅助云层参数及垂直能见度的反演并验证去噪效果。经大量不同天气条件下的实验数据验证及反演结果对比，发现该方法在保留有用信息特征、有效抑制各种平稳或非平稳噪声的基础上，能够帮助云底云高识别及能见度反演，并且降低了云高漏报率、提高了云底云高的细节识别能力和能见度反演的精度。

A denoising method combined with Hilbert-Huang transform (HHT) time-frequency analysis for backscatter signal of laser diode ceilometer based on HHT and Savitzky-Golay filtering is proposed. Considering characteristics of ceilometer backscatter signal proper structure of adaptive time-variant time-space filtering bank (TFB) assisted by Savitzky-Golay filtering is selected to suppress noise. Then, HHT time-frequency analysis is used to observe signal features and test denoising effect. It is proved by plenty of test data under various weather conditions that the method can help to suppress noise without deteriorating signal features and improve the ability of cloud base and height identification, and finally obtain precise retrieving of vertical visibility.