基于GPR的机场跑道钢筋回波检测与抑制
|
摘要
钢筋强反射回波及其多次波严重影响探地雷达在机场跑道灾害目标检测与识别的应用。本文研究机场跑道钢筋回波检测及抑制的方法。首先利用Hyp-curvelet变换将GPR时空二维回波信号投影到尺度空间,目标回波的能量将聚集且与其他目标分离,进而基于尺度空间中的局部峰值进行目标检测。然后结合目标回波的初始相位及时频特征,在尺度空间中消除钢筋回波分量。最后将数据反变换回时空域,得到只含有灾害目标回波的数据。仿真实验表明,本文所提算法在低信噪比的情况下对钢筋回波检测与抑制能取得很好的效果,重构的结果中灾害目标回波保存完整且钢筋回波罕有残余。
Strong rebar echo and its multiples will affect the performance of GPR(Ground penetrating radar) in disease target detection and discrimination badly,so they must be eliminated as much as possible.A method for rebar echo detection and suppression is proposed in this paper.First of all,GPR observed data are projected into Hyp-curvelet space by the Hyp-curvelet transform,and echoes from different targets are concentrated but separated with each other.Target can be detected by searching the peak values in Hypcurvelet space.Rebar can be discriminated from disease target with initial phase of echo and features distribution in time-frequency domain, and then its echo can be eliminated in Hyp-curvelet space.In the end,data are reconstructed back into time-space domain without containing rebar echo.Simulation results show that the proposed method has good performance in rebar echo detection and suppression under the condition of low SNR,and diseases echoes are preserved well and rebar echo is rarely left over in the reconstructed data.
Strong rebar echo and its multiples will affect the performance of GPR(Ground penetrating radar) in disease target detection and discrimination badly,so they must be eliminated as much as possible.A method for rebar echo detection and suppression is proposed in this paper.First of all,GPR observed data are projected into Hyp-curvelet space by the Hyp-curvelet transform,and echoes from different targets are concentrated but separated with each other.Target can be detected by searching the peak values in Hypcurvelet space.Rebar can be discriminated from disease target with initial phase of echo and features distribution in time-frequency domain, and then its echo can be eliminated in Hyp-curvelet space.In the end,data are reconstructed back into time-space domain without containing rebar echo.Simulation results show that the proposed method has good performance in rebar echo detection and suppression under the condition of low SNR,and diseases echoes are preserved well and rebar echo is rarely left over in the reconstructed data.
引文
[1]庞希斌,徐进,卢小兵,张爱辉.地质雷达在机场跑道缺陷检测中的应用——以“5·12”汶川地震后九寨黄龙机场检测为例[J].西南民族大学学报.2008,34 (6):1096-1100. Pang X.B,Xu J,Lu X.B,Zhang A.H.Application of the ground penetrating radar to the inspection of the airfield runway defect Taking the detection of Jiuhuang Airport after the 5.12 Wenchuan earthquake for example [J].Journal of Southwest University for Nationalities Natural Science Edition.2008,34(6):1096-1100.(in Chinese)
[2]刘喜武,刘洪,李幼铭.高分辨率Radon变换方法及其在地震信号处理中的应用[J].地球物理学进展. 2004,19(1):8-15. Liu X.W,Liu H,Li Y.M.High resolution radon trans- form and its application in seismic signal processing.Progress in Geophysics.2004,19(1):8-15.(in Chinese)
[3]张建贵.Hyp-curvelet变换与多次波的识别[D],分离和压制.长沙:中南大学地球科学与信息物理学院. 2002年7月. Zhang J.G.Hyp-curvelet frame and Multiple Waves recognition、Separation and Elimination[D].Changsha:Department of Geodetection and Information Technology, Central South University,2002.(in Chinese)
[4]Zhang R.F,Tadeusz J.Ulrych.Physical wavelet frame denoising [J].Geophysics,2003,Vol.68,No.1,pp.225- 231.
[5]孙学文,陈文超,高静怀,包乾宗.小波域强面波衰减方法研究.石油地球物理勘探.2008,43(1):22-28. Sun X.W,Chen W.C,Gao J.H,Bao Q.Z.Study on attenuation of strong surface wave in wavelet domain[J]. OGP,2008,43(1 ):22-28.(in Chinese)
[6]Timofey Grigorievich Savelyev,Luc van Kempen,and Hichem Sahli,“Investigation of Time-Frequency Features for GPR Landmine Discrimination,”IEEE Trans.Geosci.Remote Sens.,January 2007,vol.45,No.4,pp.118-129.
[7]Ingrid Daubechies.Ten Lectures on Wavelets[M].Society for Industrial and Applied Mathematics,1992,56- 102.
[8]Noor Atinah Ahmad.A Globally Convergent Stochastic Pairwise Conjugate Gradient-Based Algorithm for Adaptive Filtering [J].IEEE signal processing letters,2009,15:914- 917.
[2]刘喜武,刘洪,李幼铭.高分辨率Radon变换方法及其在地震信号处理中的应用[J].地球物理学进展. 2004,19(1):8-15. Liu X.W,Liu H,Li Y.M.High resolution radon trans- form and its application in seismic signal processing.Progress in Geophysics.2004,19(1):8-15.(in Chinese)
[3]张建贵.Hyp-curvelet变换与多次波的识别[D],分离和压制.长沙:中南大学地球科学与信息物理学院. 2002年7月. Zhang J.G.Hyp-curvelet frame and Multiple Waves recognition、Separation and Elimination[D].Changsha:Department of Geodetection and Information Technology, Central South University,2002.(in Chinese)
[4]Zhang R.F,Tadeusz J.Ulrych.Physical wavelet frame denoising [J].Geophysics,2003,Vol.68,No.1,pp.225- 231.
[5]孙学文,陈文超,高静怀,包乾宗.小波域强面波衰减方法研究.石油地球物理勘探.2008,43(1):22-28. Sun X.W,Chen W.C,Gao J.H,Bao Q.Z.Study on attenuation of strong surface wave in wavelet domain[J]. OGP,2008,43(1 ):22-28.(in Chinese)
[6]Timofey Grigorievich Savelyev,Luc van Kempen,and Hichem Sahli,“Investigation of Time-Frequency Features for GPR Landmine Discrimination,”IEEE Trans.Geosci.Remote Sens.,January 2007,vol.45,No.4,pp.118-129.
[7]Ingrid Daubechies.Ten Lectures on Wavelets[M].Society for Industrial and Applied Mathematics,1992,56- 102.
[8]Noor Atinah Ahmad.A Globally Convergent Stochastic Pairwise Conjugate Gradient-Based Algorithm for Adaptive Filtering [J].IEEE signal processing letters,2009,15:914- 917.
版权所有：© 2023 中国地质图书馆 中国地质调查局地学文献中心