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An EMD-based denoising method for lidar signal

机译:基于EMD的激光雷达信号去噪方法

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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 possible to be reduced. In this 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.
机译:激光雷达回波信号是典型的非稳态,非平稳信号,传统的滤波方法难以处理。作为近年来提出的一种新的信号处理理论,经验模态分解方法可以根据不同的时间尺度将激光雷达回波信号自适应地划分为不同的固有模式函数(IMF)分量,而噪声主要集中在高频分量上。然而,当仅去除高频成分进行滤波时,有用信号将可能被减少。提出了一种结合经验模态分解(EMD)和Savitzky-Golay滤波器的新方法。通过实验表明,我们的方法不仅可以有效地去除噪声成分,而且可以保持有用的信号,然后将在下一阶段的数据处理中提高准确性。

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