|Table of Contents|

[1] Ji Xunsheng, Wang Shourong, Xu Yishen, et al. Application of fast wavelet transformationin signal processing of MEMS gyroscope [J]. Journal of Southeast University (English Edition), 2006, 22 (4): 510-513. [doi:10.3969/j.issn.1003-7985.2006.04.014]
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Application of fast wavelet transformationin signal processing of MEMS gyroscope()
快速小波变换在MEMS陀螺信号处理中的应用
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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
22
Issue:
2006 4
Page:
510-513
Research Field:
Automation
Publishing date:
2006-12-30

Info

Title:
Application of fast wavelet transformationin signal processing of MEMS gyroscope
快速小波变换在MEMS陀螺信号处理中的应用
Author(s):
Ji Xunsheng1;  2;  Wang Shourong1;  Xu Yishen1
1 School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China
2 School of Communication & Control, Southern University, Wuxi 214063, China
吉训生1;  2;  王寿荣1;  许宜申1
1东南大学仪器科学与工程学院, 南京 210096; 2江南大学信控学院, 无锡 214063
Keywords:
wavelet transformation;  signal processing;  gyroscope;  threshold
小波变换;  信号处理;  陀螺;  阈值
PACS:
TP206+.1
DOI:
10.3969/j.issn.1003-7985.2006.04.014
Abstract:
Decomposition and reconstruction of Mallat fast wavelet transformation(WT)is described.A fast algorithm, which can greatly decrease the processing burden and can be very easy for hardware implementation in real-time, is analyzed.The algorithm will no longer have the processing of decimation and interpolation of usual WT.The formulae of the decomposition and the reconstruction are given.Simulation results of the MEMS(micro-electro mechanical systems)gyroscope drift signal show that the algorithm spends much less processing time to finish the de-noising process than the usual WT.And the de-noising effect is the same.The fast algorithm has been implemented in a TMS320C6713 digital signal processor.The standard variance of the gyroscope static drift signal decreases from 78.435 5(°)/h to 36.763 5(°)/h.It takes 0.014 ms to process all input data and can meet the real-time analysis of signal.
介绍了Mallat快速小波分解和重构算法, 分析了一种可以大大降低运算负担, 并且十分易于硬件实时实现的快速算法.该算法不再需要小波变换过程中的内插和抽取步骤, 给出了相应的分解和重构过程的公式.对MEMS陀螺仪测量信号的仿真结果表明:算法只需更短的处理时间就可以完成去噪声过程, 并且可以取得同样的去噪效果.在TMS320C6713芯片上实现了该算法, 每个数据的处理时间只需0.014 ms, 静态漂移信号的标准差也从78.435 5(°)/h降到36.763 5(°)/h, 完全可以满足信号实时处理的需要.

References:

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Memo

Memo:
Biographies: Ji Xunsheng(1969—), male, graduate;Wang Shourong(corresponding author), male, doctor, professor, srwang@seu.edu.cn.
Last Update: 2006-12-20