Chinese Journal of Lasers, Volume. 41, Issue 10, 1014001(2014)

An Empirical Mode Decomposition Algorithm Based on Cross Validation and Its Application to Lidar Return Signal De-Noising

Wang Huanxue1,2、*, Liu Jianguo1, Zhang Tianshu1, and Dong Yunsheng1
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  • 1[in Chinese]
  • 2[in Chinese]
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    Noise reduction method of lidar atmospheric backscattering signal based on empirical mode decomposition (EMD) is developed by Cross-Validation. Considering characteristics of lidar return signal noise and defects of traditional de-noising algorithm, Cross-Validation is applied to identify signal layers and noise layers automatically, and then separate signal and noise by EMD reconstruction. With experiments, the method can select the signal in the instrinsic mode function adaptively, not only removes the random error, but also maintains the effective characteristics of the signal, reduces the loss of signal, and then improve the accuracy in the next phase of data processing.

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    Wang Huanxue, Liu Jianguo, Zhang Tianshu, Dong Yunsheng. An Empirical Mode Decomposition Algorithm Based on Cross Validation and Its Application to Lidar Return Signal De-Noising[J]. Chinese Journal of Lasers, 2014, 41(10): 1014001

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    Paper Information

    Category: Remote Sensing and Sensors

    Received: Mar. 21, 2014

    Accepted: --

    Published Online: Aug. 12, 2014

    The Author Email: Huanxue Wang (hxwang@aiofm.ac.cn)

    DOI:10.3788/cjl201441.1014001

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