一种改进的探地雷达回波信号的奇异性检测
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摘要
利用相邻道信号具有相似性的特征,对探地雷达回波信号,采用地震勘探奇异性检测的方法,运用二进小波变换的模极大值,提出了一种改进的、基于相关道奇异性检测的算法并予以实现.分别使用原小波变换奇异性检测算法和相关道奇异性检测算法,对一组探地雷达正演分层回波数据进行处理.处理结果表明,改进的方法较原方法能够更准确地检测出探地雷达回波信号的奇异点,能更好地去除噪声和其他因素对信号的干扰以及发现地下异常.改进算法对奇异性检测具有显著的优越性,为目标识别和图像重构等后继处理提供了有力的支持.
By means of the characteristic that neighboring scan signal has similarity, basing on the singularity detection of seismic trace, using the module maxima of binary wavelet transform,the paper presents an new improved algorithm and application about the singularity detection of neighboring scan, which can be applied into GPR echo signal. Furthermore, by providing a set of processing results on the GPR stratified echo signal, this improved algorithm,compared with the old algorithm, can detect the singularity of GPR echo signal, restrain the noise's and other disturbance more efficiently and find underground exception. It has remarkable superiority to singularity detection.And it provides powerful supports for later procession, such as object identification, image reconstruction and so on.
By means of the characteristic that neighboring scan signal has similarity, basing on the singularity detection of seismic trace, using the module maxima of binary wavelet transform,the paper presents an new improved algorithm and application about the singularity detection of neighboring scan, which can be applied into GPR echo signal. Furthermore, by providing a set of processing results on the GPR stratified echo signal, this improved algorithm,compared with the old algorithm, can detect the singularity of GPR echo signal, restrain the noise's and other disturbance more efficiently and find underground exception. It has remarkable superiority to singularity detection.And it provides powerful supports for later procession, such as object identification, image reconstruction and so on.
引文
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[2] DaubechiesI.TheWaveletTransform,TimeFrequencyLocalizationandSignalAnalysis[J].IEEETransonInformationTheory,1990,36(5):961 1005.
[3] GrossmanA.WaveletTransformandEdgeDetection[J].StochasticProcessesinPhysicsandEngineering,1986,16:458 472.
[4] MallatS,ZhongS.CharacterizationofSignalsfromMulti scaleEdges[J].IEEETransPartAnalandMathIntell,1992,14(7):710 732.
[5] 胡寿松,周川,胡维礼.基于小波奇异性的结构故障检测[J].应用科学学报,2000,18(3):198 201.HuShou song,ZhouChuan,HuWei li.FaultDiagnosisStrategyBasedonWaveletSingularityDetection[J].JournalofAppliedScience,2000,18(3):198 201(Ch).
[6] 郑继明.小波变换在地震道奇异性检测中的应用[J].重庆邮电学院学报,1997,9(1):66 69.ZhenJi ming.DetectingtheSingularityofSeismicTracewithWaveletTransform[J].JournalofChongqingUniversityofPostsandTelecommunications,1997,9(1):66 69(Ch).
[7] 赵学智,林颖,陈文戈,等.奇异性信号检测时小波基的选择[J].华南理工大学学报(自然科学版),2000,28(10):75 80.ZhaoXue zhi,LinYing,ChenWen ge,etal.TheChoiceofWaveletBasesforSingularSignalDetection[J].JournalofSouthChinaUniversityofTechnology(NaturalScienceEdition),2000,28(10):75 80(Ch).
[8] MallatS,WenL.SingularityDetectionandProcessingwithWavelets[J].IEEETransactionTheory,1992,38(2):617 643.
[9] 杨福生.小波变换的工程分析与应用[M].北京:科学出版社,1999.YangFS.WaveletTransforminProjectAnalysisandApplications[M].Beijing:SciencePress,1999(Ch).
[10]秦前清,杨宗凯.实用小波分析[M].西安:西安电子科技大学出版社,1995.QingQian qing,YangZong kai.PracticalAnalysisofWavelet[M].Xi′an:XidianUniversityPress,1995(Ch).
[11]DavidL,IainM.ThresholdSelectionforWaveletShrinkageofNoisyData[J].Proceedingsofthe16thAnnualInternationalConferenceoftheIEEE,1994,1:A24A25.
[12]顾建农,张志宏,吴正国,等.基于小波变换模极大值恢复的信号消噪方法[J].海军工程大学学报,2001,13
(2):25 32.GuJian nong,ZhongZhi hong,WuZheng guo,etal.ASignalDenoisingAlgorithmBasedontheWaveletTransformModulusMaxima[J].JournalofNavalUniversityofEngineering,2001,13(2):25 32(Ch).
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