An EMD-based denoising method for lidar signal

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 intr...

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Bibliographic Details
Published in2010 3rd International Congress on Image and Signal Processing Vol. 8; pp. 4016 - 4019
Main Authors YiKun Zhang, XiaoChang Ma, DengXin Hua, YingAn Cui, LianSheng Sui
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2010
Subjects
Denoising
Empirical mode decomposition
Filtering
Laser radar
Lidar
Noise
Noise reduction
Optical filters
Savitzky-Golay
Signal processing algorithms
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Summary: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.
ISBN:1424465133
9781424465132
DOI:10.1109/CISP.2010.5648129