几种重排算法在地震信号处理中的实验分析
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摘要
阐述了时频分析技术中重排算法的基本思想,给出了部分重排算法的局部能量重心表达式;设计了两个数值实验,利用几种重排算法对单道地震信号进行了计算和分析比较。结果表明:重排算法不仅能有效抑制交叉项,同时也能提高时频聚集性,从而获得更理想的局部信号特征。其中以重排Spectrogram分布的时频聚集能力最佳,尤其适合于突出主频信号;重排平滑伪Wigner-Ville分布同样也能够获得较理想的时频效果,但稍弱于前一种方法;重排伪MH分布的时频聚集性相对较差,没有对分散的能量进行有效的重新分配处理。重排算法因其突出的时频聚集能力,应用在地震剖面中可以得到更加细致的瞬时频率特征。
The main idea of reassignment method in time-frequency analysis is presented and some expressions used to compute the accurate location of the local energy gravity center are given;then two numerical experiments are presented to show how these reassignment methods work individually as used to process single-trace seismic data.Based on the experiments,some conclusions are drawn that the reassignment methods can not only effectively reduce cross-terms,but also lead to a good time-frequency concentration.Compared with others,the reassignment spectrogram has the best potential for ideal time-frequency concentration,especially when the dominant frequencies are required to be underlined.The reassignment smoothing pseudo Wigner-Ville distribution can also achieve perfect effects though it is a little worse than the former one.The pseudo Margenau-Hill distribution is the worst of the three,since it fails to relocate the dispersive energy to the calculated center.A pretty precise instantaneous frequency section can be produced when the reassignment method is applied to deal with seismic signals.
The main idea of reassignment method in time-frequency analysis is presented and some expressions used to compute the accurate location of the local energy gravity center are given;then two numerical experiments are presented to show how these reassignment methods work individually as used to process single-trace seismic data.Based on the experiments,some conclusions are drawn that the reassignment methods can not only effectively reduce cross-terms,but also lead to a good time-frequency concentration.Compared with others,the reassignment spectrogram has the best potential for ideal time-frequency concentration,especially when the dominant frequencies are required to be underlined.The reassignment smoothing pseudo Wigner-Ville distribution can also achieve perfect effects though it is a little worse than the former one.The pseudo Margenau-Hill distribution is the worst of the three,since it fails to relocate the dispersive energy to the calculated center.A pretty precise instantaneous frequency section can be produced when the reassignment method is applied to deal with seismic signals.
引文
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[20]王浩,张来斌.ISVD降噪和重排谱图在烟机信号HHT时频谱分析中的应用[J].仪器仪表学报,2009,30(3):615-620.
[21]田岩,苟彦新,池万红.基于重排方法的跳频信号分析研究[J].通信对抗,2007,96(1):8-12.
[22]AUGER F,FLANDRIN P.Improving the readability of time-frequencyand time-scale representations by the reassignment method[J].IEEE Transactions on Signal Processing,1995,43(5):1068-1089.
[23]MOYAL J E.Quantum mechanics as statistical theory[J].Proc.Camb.Phil.Soc.,1949(45):99-124.
[24]蔡希玲,吕英梅.地震数据时频分析与分频处理[J].勘探地球物理进展,2005,28(4):265-270.
[25]FLANDRIN P,MARTIN W.A general class of estimators for theWigner-Ville spectrum of nonstationary processes[R].Berlin:[s.n.],1984:15-23.
[26]姜鸣,陈进,汪慰军.几种Cohen类时频分布的比较及应用[J].机械工程学报,2003,8(39):129-134.
[27]HIPPENSTIEL R D,OLIVEIRA P M.Time varying spectralestimation using the instantaneous power spectrum(IPS)[J].IEEE Trans Acoust,1990(38):1752-1759.
[2]刘振峰,郝天珧,王峰,等.地震资料在层序地层学中的应用进展[J].地球物理学进展,2003,18(1):24-29.
[3]邹文,陈爱萍,顾汉明.地震信号的时频分析方法[J].世界地质,2004,23(1):97-99.
[4]李小梅,俞娟丽.时频分析技术在层序旋回划分中的应用[J].石油与天然气地质,2008,29(6):793-796.
[5]IVAN M C.Empirical mode decomposition based time-frequencyattributes[A].Houston:SEG 1999 Annual Meeting,1999.
[6]闫述,陈明生.瞬变电磁场资料的联合时频分析解释[J].地球物理学报,2005,48(1):203-208.
[7]JONE D,BARANIUK R.An adaptive optimum kernel time-frequencyrepresentation[J].IEEE Trans.Signal Processing,1995,43(10):2361-2371.
[8]朱晓明,薛荣俊,刘喜武,等.时频分析在地震数据处理中的应用[J].内蒙古石油化工,2007,17(8):97-99.
[9]宋士琼,钟子发,陈旗.基于非线性时频分布的跳频信号分析研究[J].计算机仿真,2005,22(8):270-273.
[10]吕金飞,程乃平,袁嗣杰.非线性时频分布重排算法在非合作跳频信号检测中的应用[J].装备指挥技术学院学报,2007,18(4):78-83.
[11]吴小羊,刘天佑.基于时频重排的地震信号Wigner-Ville分布时频分析[J].石油地球物理勘探,2009,2(44):201-205.
[12]单娜琳,程志平,丁彦礼.地震映像数据的时频分析方法及应用[J].地球物理学进展,2007,22(6):1740-1745.
[13]杨培杰,印兴耀,张广智.希尔伯特-黄变换地震信号时频分析与属性提取[J].地球物理学进展,2007,22(5):1585-1590.
[14]李春峰,LINER C.基于小波多尺度分析的奇性指数:一种新地震属性[J].地球物理学报,2005,48(4):882-888.
[15]刘喜武,张宁,勾永峰,等.地震勘探信号时频分析方法对比与应用分析[J].地球物理学进展,2008,23(3):743-752.
[16]BARANIUK R G,JONES D L.A radial-gaussian,signal-dependenttime-frequency analysis using kernel[J].Signal Processing,1993,32(6):263-284.
[17]夏云龙,朴胜春,付永庆.一种基于时间反转镜和Wigner-Houg变换的线性调频信号检测方法[J].中南大学学报(自然科学版),2009,40(3):719-724.
[18]VELEZ E F,ABSHER R G.Spectral estimation based on theWigner-Ville representation[J].Signal Processing,1990,20(4):325-346.
[19]王强,潘翔.面向沉底目标的分数阶傅里叶变换谱重排回波时频处理[J].中南大学学报(自然科学版),2009,40(6):1649-1654.
[20]王浩,张来斌.ISVD降噪和重排谱图在烟机信号HHT时频谱分析中的应用[J].仪器仪表学报,2009,30(3):615-620.
[21]田岩,苟彦新,池万红.基于重排方法的跳频信号分析研究[J].通信对抗,2007,96(1):8-12.
[22]AUGER F,FLANDRIN P.Improving the readability of time-frequencyand time-scale representations by the reassignment method[J].IEEE Transactions on Signal Processing,1995,43(5):1068-1089.
[23]MOYAL J E.Quantum mechanics as statistical theory[J].Proc.Camb.Phil.Soc.,1949(45):99-124.
[24]蔡希玲,吕英梅.地震数据时频分析与分频处理[J].勘探地球物理进展,2005,28(4):265-270.
[25]FLANDRIN P,MARTIN W.A general class of estimators for theWigner-Ville spectrum of nonstationary processes[R].Berlin:[s.n.],1984:15-23.
[26]姜鸣,陈进,汪慰军.几种Cohen类时频分布的比较及应用[J].机械工程学报,2003,8(39):129-134.
[27]HIPPENSTIEL R D,OLIVEIRA P M.Time varying spectralestimation using the instantaneous power spectrum(IPS)[J].IEEE Trans Acoust,1990(38):1752-1759.
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