激光雷达回波信号是典型的非稳态、 非平稳信号， 用传统的滤波方法难以对其进行有效地处理。 利用经验模式分解方法（EMD）将信号按照不同的特征时间尺度分解为不同的IMF分量， 将含有噪声的高频IMF分量剔除， 可达到去噪的目的。 但如果简单地将高频分量直接剔除， 有可能造成有效信号的损失。 可提出将EMD方法与Savitzky-Golay滤波器（DISPO）结合的方法， 该方法能在保证信号完整性的同时， 对原始信号进行有效处理。 经仿真数据与实测数据的实验对比分析， 该方法不但有效地去除噪声信号， 而且尽可能地保持了有效信号， 减少了信号损失， 提高了数据处理的准确度。

Lidar echo signal is a typical non-steady-state, non-stationary signal, and difficult to be dealt with by the traditional filtering methods. As a new signal processing theory proposed in recent years, empirical mode decomposition method can adaptively divide the lidar echo signal into different intrinsic mode function (IMF) components according to different time scale, and noise mainly concentrates in the high-frequency component. However, when filtered with simply removing high frequency component, the useful signal will be possibly reduced. In the present paper, a new method which combines empirical mode decomposition (EMD) with Savitzky-Golay filter is proposed. With experiments, it is indicated that our approach not only removes the noise component effectively but also maintains the useful signal, then will improve the accuracy in the next phase of data processing.