分数维约束下的自适应对消技术研究
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摘要
介绍了自适应对消技术的基本原理,分析了自适应对消技术的优缺点,针对一些缺点提出了相应的改进方法。由于常规自适应对消技术是通过迭代技术实现的,需要迭代一定次数后才能确定最佳参数,所以在信号起始位置和有效信号尾部收敛效果不好,从而影响滤波效果。引入hausdorff维数来约束地震信号,首先求取原始地震信号的hausdorff维数谱,利用有效信号与随机噪音维数的不同,将有效信号以外的随机噪音滤除,并将自适应对消中的参考噪声对应位置的随机噪音去除;然后将更新后的地震信号和参考噪声进行自适应滤波,从而得到一个优化的自适应对消滤波器。
This article describes the basic principles of the adaptive cancellation technology, analysis the advantages and disadvantages of the adaptive cancellation technology, and proposes some corresponding improvement methods about the shortcomings of the adaptive cancellation technology. Since the conventional adaptive cancellation techniques are realized by iteration and need some times to make sure the best parameters,so the starting position of the signal and the tail of the effective signal are not well convergence, thus affecting the filtering effect. The paper used the hausdorff dimension constrain the seismic signal. Firstly, the paper computes the hausdorff dimension of the original seismic signal, and then filters the random noise beyond of the effective signal and the random noise at the relative position in the referenced noise based on the difference of the hasusdorff dimension about the effective signal and random noise; secondly, the paper updates the seismic signal and referenced noise to be adaptive filter, and gains an optimized adaptive cancellation filter.
This article describes the basic principles of the adaptive cancellation technology, analysis the advantages and disadvantages of the adaptive cancellation technology, and proposes some corresponding improvement methods about the shortcomings of the adaptive cancellation technology. Since the conventional adaptive cancellation techniques are realized by iteration and need some times to make sure the best parameters,so the starting position of the signal and the tail of the effective signal are not well convergence, thus affecting the filtering effect. The paper used the hausdorff dimension constrain the seismic signal. Firstly, the paper computes the hausdorff dimension of the original seismic signal, and then filters the random noise beyond of the effective signal and the random noise at the relative position in the referenced noise based on the difference of the hasusdorff dimension about the effective signal and random noise; secondly, the paper updates the seismic signal and referenced noise to be adaptive filter, and gains an optimized adaptive cancellation filter.
引文
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[9]Mandelbrot B B.The Fractal Geometry of Nature[M].San Francisco:W.H.Freeman and Company,1982.
[10]陈波.自适应滤波技术研究及其应用[D].武汉:武汉理工大学,2010.
[11]陈莉.自适应滤波算法与应用研究[D].西安:西安电子科技大学,2006.
[12]杨振.基于分数维的自适应滤波去噪方法研究[D].北京:中国地质大学,2012.
[2]Boschetti F,Dentith M D,List R D.A fractal-based algorithm for detecting first arrivals on seismic traces[J].Geophysics,1996,61(4):1095-1102.
[3]常旭,刘伊克.Hausdorff分数维识别地震道初至走时[J].地球物理学报,1998,41(6):826-832.
[4]常旭,刘伊克.地震记录的广义分维及其应用[J].地球物理学报,2002,45(6):839-846.
[5]魏巍,刘学伟.自适应噪声抵消技术的仿真与应用研究[J].计算机仿真,2009,26(2):358-361.
[6]苗文广.频率域自适应滤波技术及其应用[D].吉林:吉林大学,2005:20-29.
[7]曹斌芳.自适应噪声抵消技术的研究[D].湖南:湖南大学,2007:6-38.
[8]牛滨华,沈操,黄新武.波动方程多次波压制技术的进展[J].地球物理学进展,2002,17(3):480-485.
[9]Mandelbrot B B.The Fractal Geometry of Nature[M].San Francisco:W.H.Freeman and Company,1982.
[10]陈波.自适应滤波技术研究及其应用[D].武汉:武汉理工大学,2010.
[11]陈莉.自适应滤波算法与应用研究[D].西安:西安电子科技大学,2006.
[12]杨振.基于分数维的自适应滤波去噪方法研究[D].北京:中国地质大学,2012.
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