[1]赵立业,李宏生,周百令,等.基于形态小波的高精度重力仪信号快速滤波算法[J].东南大学学报(自然科学版),2010,40(6):1217-1221.[doi:10.3969/j.issn.1001-0505.2010.06.017]
 Zhao Liye,Li Hongsheng,Zhou Bailing,et al.in precise gravimeter signal processing[J].Journal of Southeast University (Natural Science Edition),2010,40(6):1217-1221.[doi:10.3969/j.issn.1001-0505.2010.06.017]
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基于形态小波的高精度重力仪信号快速滤波算法()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
40
期数:
2010年第6期
页码:
1217-1221
栏目:
仪器科学与技术
出版日期:
2010-11-20

文章信息/Info

Title:
in precise gravimeter signal processing
作者:
赵立业 李宏生 周百令 李坤宇
东南大学仪器科学与工程学院,南京 210096; 东南大学微惯性仪表与先进导航技术教育部重点试验室, 南京 210096
Author(s):
Zhao Liye Li Hongsheng Zhou Bailing Li Kunyu
School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China
Key Laboratory of Micro Inertial Instrument and Advanced Navigation Technology of Ministry of Education, Southeast University, Nanjing 210096, China
关键词:
重力仪 信号处理 形态小波滤波 FFT
Keywords:
gravimeter signal processing morphological wavelet filter fast Fourier transformation
分类号:
X502
DOI:
10.3969/j.issn.1001-0505.2010.06.017
摘要:
为了有效抑制高精度重力测量信号中的各种强噪声以获得高精度重力信息,在分析形态小波滤波算法的基础上,结合FFT算法提出了一种快速形态小波滤波算法,并应用于高精度重力仪信号处理中.在滤波过程中,首先在常规小波分解算法各层间增加形态滤波器,以提高小波算法抑制脉冲干扰的能力.然后,将常规小波分解和重构算法进行重组,并参考FFT算法规则设计了一种快速形态小波分解重构算法,以提高小波分解和重构的计算效率.最后,通过仿真试验,将快速形态小波滤波算法与传统小波滤波算法进行性能对比.理论分析和仿真试验结果表明,快速形态小波算法的滤波效果优于传统小波滤波,其运算速度优于Mallat算法.
Abstract:
Combined with the fast Fourier transformation(FFT)method, a fast morphological wavelet filter algorithm is proposed based on the morphological wavelet algorithm and applied to the precise gravimeter signal processing in order to suppress serious background noises and get high precise gravity information. The preliminary work is to add the morphological filter to each level of the classical wavelet decomposition to suppress the impulse noise. Then, the regular wavelet decomposition and reconstruction algorithms are reconstructed. With reference to the FFT method, the fast morphological wavelet decomposition and reconstruction algorithms are designed to increase the computational efficiency. Finally, the performances of the fast morphological wavelet filter and the classical wavelet filter are compared by simulation. Theoretical analysis and simulation results show that the denoising performance of the proposed method is better than that of the classical wavelet algorithm and the computation speed is superior to that of the classical Mallat algorithm.

参考文献/References:

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备注/Memo

备注/Memo:
作者简介: 赵立业(1977—),男,博士,副教授; 李宏生(联系人),男,教授,博士生导师,hsli@seu.edu.cn.
基金项目: 国家自然科学基金资助项目(60575010,40804015)、高等学校博士学科点专项科研基金资助项目(20070286067,200802861060).
引文格式: 赵立业,李宏生,周百令,等.基于形态小波的高精度重力仪信号快速滤波算法[J].东南大学学报:自然科学版,2010,40(6):1217-1221. [doi:10.3969/j.issn.1001-0505.2010.06.017]
更新日期/Last Update: 2010-11-20