地质雷达信号分析的双正交小波预测反褶积法
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TN959.71

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国家自然科学基金(51678071、51278071);长沙理工大学桥梁工程领域开放基金(14KC06);长沙理工大学研究生科研创新项目(CX2015BS02)


A predictive deconvolution method based on biorthogonal wavelet of GPR signal analysis
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    摘要:

    为了降低电磁波衰减、噪声干扰等因素对地质雷达检测效果的影响,提出一种双正交小波预测反褶积法(PDBW法)。在PDBW法中,针对地质雷达检测信号选取具有最小重构误差的双正交小波基,运用该小波基将地质雷达检测信号分解成不同频段的时域子信号,对各频段的时域子信号进行预测反褶积等滤波处理,再对处理后的子信号进行重构变换,得到PDBW法的处理结果。将PDBW法用于实验检测信号处理,并将处理结果与预测反褶积法的处理结果进行比较,结果表明:PDBW法能有效压制多次回波干扰,准确识别深部信号,显著提高深部信号信噪比,从而进一步改善地质雷达探测分辨率和图像分析的准确性。

    Abstract:

    In order to reduce the influence of some factors such as the electromagnetic wave attenuation and noise jamming on detection effect of GPR, a predictive deconvolution method based on biorthogonal wavelet was proposed (short for PDBW method). In the PDBW method, the biorthogonal wavelet basis with the minimum reconstruction error for detection signal of GPR was chosen, using this wavelet to decompose the GPR signals into different frequency band sub-signals, and then predictive deconvolution and other filter method were used to deal with each frequency band sub-signal in time domain, at last the results of PDBW method by reconstructing each sub-signal were get. Using the PDBW method to deal with the detection signal of experiment, the results show that, comparing with the predictive deconvolution, the PDBW method could restrain the multiple echo interference, identify the deep signal precisely, and enhance the signal to noise ratio of deep signal, thus improving the detecting resolution and the accuracy of image analysis of GPR signal.

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凌同华,刘浩然,谷淡平,张亮.地质雷达信号分析的双正交小波预测反褶积法[J].土木与环境工程学报(中英文),2018,40(2):26-31. Ling Tonghua, Liu Haoran, Gu Danping, Zhang Liang. A predictive deconvolution method based on biorthogonal wavelet of GPR signal analysis[J]. JOURNAL OF CIVIL AND ENVIRONMENTAL ENGINEERING,2018,40(2):26-31.10.11835/j. issn.1674-4764.2018.02.005

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  • 收稿日期:2017-06-15
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  • 在线发布日期: 2018-03-08
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