地质雷达信号分析的双正交小波预测反褶积法
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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。
In order to reduce the influence of some factors such as the electromagnetic wave attenuation and noise jamming on detection effect of GPR,apredictive 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.
In order to reduce the influence of some factors such as the electromagnetic wave attenuation and noise jamming on detection effect of GPR,apredictive 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.
引文
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[2]曾昭发,刘四新,冯晅,等.探地雷达原理与应用[M].北京:电子工业出版社,2010.
[3]凌同华,张胜,李升冉.地质雷达隧道超前地质预报检测信号的HHT分析法[J].岩石力学与工程学报,2012,31(7):1422-1428.LING T H,ZHANG S,LI S R.Hilbert-huang transform method for detection signal of tunnel geological prediction using ground penetrating radar[J].Chinese Journal of Rock Mechanics and Engineering,2012,31(7):1422-1428.(in Chinese)
[4]BERNATEK-JAKIEL A,KONDRACKA M.Combining geomorphological mapping and near surface geophysics(GPR and ERT)to study piping systems[J].Geomorphology,2016,274(1):193-209.
[5]PONGSAK W,RAKTIPONG S,SOMNUK T,et al.A new method to determine locations of rebars and estimate cover thickness of RC structures using GPR data[J].Construction and Building Materials,2017,140(1):257-273.
[6]石刚,田养军,王亚琼,等.基于模糊分形脉冲反褶积的探地雷达信号处理[J].长安大学学报(自然科学版),2012,32(5):79-84.SHI G,TIAN Y J,WANG Y Q,et al.Signal processing of ground-penetrating radar on the principle of deconvolution based on fuzzy fractal pulse[J].Journal of Chang'an University(Natural Science Edition),2012,32(5):79-84.(in Chinese)
[7]苏茂鑫,李术才,薛翊国,等.基于反褶积的探地雷达高分辨率处理方法[J].浙江大学学报(工学版),2010,44(6):1201-1206.SU M X,LI S C,XUE Y G.Ground penetrating radar’s high resolution processing method based on deconvolution[J].Journal of Zhejiang University(Engineering Science),2010,44(6):1201-1206.(in Chinese)
[8]ECONOMOU N,VAFIDIS A.GPR data time varying deconvolution by kurtosis maximization[J].Journal of Applied Geophysics,2012(81):117-121.
[9]王万里,杨午阳,魏新建,等.随机稀疏脉冲非线性反褶积[J].地球物理学进展,2014,29(4):1780-1784.WANG W L,YANG W Y,WEI X J,et al.Stochastic sparse spike nonlinear deconvolution[J].Progress in Geophysics,2014,29(4):1780-1784.(in Chinese)
[10]CHANG Y F,MA Y,LIN C M,et al.Reverberation reduction in ultrasonic images via predictive deconvolution[J].NDT&E International,2008,41(4):235-241.
[11]TZANIS A.Detection and extraction of orientationand-scale-dependent information from two-dimensional GPR data with tuneable directional wavelet filters[J].Journal of Applied Geophysics,2013,89:48-67.
[12]NGUYEN S T,BRIAN W H.Bi-orthogonal rational discrete wavelet transform with multiple regularity orders and application experiments[J].Signal Processing,2013,93(11):3014-3026.
[13]MOURAD K,FETHI B R.Efficient automatic detection of QRS complexes in ECG signal based on reverse biorthogonal wavelet decomposition and nonlinear filtering[J].Measurement,2016,94:663-670.
[14]MACEDO I A S,SILVA C B,FIGUEIREDO J J S.Comparison between deterministic and statistical wavelet estimation methods through predictive deconvolution:Seismic to well tie example from the North Sea[J].Journal of Applied Geophysics,2017,136:298-314.
[15]FLETCHER P,SANGWINE S J.The development of the quaternion wavelet transform[J].Singal Procsessing,2017,136:2-15.
[16]成谢锋,张正.一种双正交心音小波的构造方法[J].物理学报,2013,62(16):168701.CHENG X F,ZHANG Z.A construction method of biorthogonal heart sound wavelet[J].Acta Physica Sinica,2013,62(16):168701.(in Chinese)
[17]HACHICHA W,KAANICHE M,BEGHDADI A,et al.No-reference stereo image quality assessment based on joint wavelet decomposition and statistical models[J].Signal Processing:Image Communication,2017,54:107-117.
[18]FENG X,LIANG W J,LIU C,et al.Application of Freeman decomposition to full polarimetric GPR for improving subsurface target classification[J].Signal Processing,2016,132:3534-3537.
[19]杨艳青,贺少辉,齐法琳,等.铁路隧道衬砌地质雷达非接触检测模拟试验研究[J].岩石力学与工程学报,2011,30(9):1761-1771.YANG Y Q,HE S H,QI F L,et al.Simulation test of GPR non-contact detection on lining of railway tunnel[J].Chinese Journal of Rock Mechanics and Engineering,2011,30(9):1761-1771.(in Chinese)
[20]胡进峰,周正欧.浅地层探地雷达目标探测和定位新方法[J].仪器仪表学报,2006,27(4):371-375.HU J F,ZHOU Z O.Target detection and orientation in sur-surface penetrating radar data[J].Chinese Journal of Scientific Instrument,2006,27(4):371-375.(in Chinese)