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    GPR Signal Denoising and Target Extraction With the CEEMD Method

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    Type
    Article
    Authors
    Li, Jing cc
    Liu, Cai
    Zeng, Zhaofa
    Chen, Lingna
    KAUST Department
    Physical Science and Engineering (PSE) Division
    Date
    2015-04-17
    Online Publication Date
    2015-04-17
    Print Publication Date
    2015-08
    Permanent link to this record
    http://hdl.handle.net/10754/622552
    
    Metadata
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    Abstract
    In this letter, we apply a time and frequency analysis method based on the complete ensemble empirical mode decomposition (CEEMD) method in ground-penetrating radar (GPR) signal processing. It decomposes the GPR signal into a sum of oscillatory components, with guaranteed positive and smoothly varying instantaneous frequencies. The key idea of this method relies on averaging the modes obtained by empirical mode decomposition (EMD) applied to several realizations of Gaussian white noise added to the original signal. It can solve the mode-mixing problem in the EMD method and improve the resolution of ensemble EMD (EEMD) when the signal has a low signal-to-noise ratio. First, we analyze the difference between the basic theory of EMD, EEMD, and CEEMD. Then, we compare the time and frequency analysis with Hilbert-Huang transform to test the results of different methods. The synthetic and real GPR data demonstrate that CEEMD promises higher spectral-spatial resolution than the other two EMD methods in GPR signal denoising and target extraction. Its decomposition is complete, with a numerically negligible error.
    Citation
    Jing Li, Cai Liu, Zhaofa Zeng, Lingna Chen (2015) GPR Signal Denoising and Target Extraction With the CEEMD Method. IEEE Geoscience and Remote Sensing Letters 12: 1615–1619. Available: http://dx.doi.org/10.1109/LGRS.2015.2415736.
    Sponsors
    This work was supported in part by the National Natural Science Foundation of China under Grants 4143000131 and 41174097 and in part by the 973 Program under Grant 2013CB429805.
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    IEEE Geoscience and Remote Sensing Letters
    DOI
    10.1109/LGRS.2015.2415736
    ae974a485f413a2113503eed53cd6c53
    10.1109/LGRS.2015.2415736
    Scopus Count
    Collections
    Articles; Physical Science and Engineering (PSE) Division

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