声表面波谐振器回波信号的频率估计

刘伯权; 郭佳佳; 罗治民

doi:10.11999/JEIT180875

声表面波谐振器回波信号的频率估计

doi: 10.11999/JEIT180875

湘潭大学物理与光电工程学院湘潭 411100

基金项目: 国家自然科学基金(61601395)

详细信息

作者简介:
刘伯权：男，1985年生，讲师，主要研究方向为无线无源声表面波传感器超分辨率测量方法研究、集成电路设计等

郭佳佳：男，1993年生，硕士生，信号处理与超分辨率研究等

罗治民：男，1991年生，硕士生，集成电路设计

通讯作者:
郭佳佳　stujiajia@126.com

中图分类号: TN911.72
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- 被引次数: 0
出版历程
- 收稿日期: 2018-09-07
- 修回日期: 2019-02-18
- 网络出版日期: 2019-03-13
- 刊出日期: 2019-09-10

Surface Acoustic Wave Resonator Echo Signal Frequency Estimation

Institute of Physical and Optoelectronic Engineering, Xiangtan University, Xiangtan 411100, China

Funds: The National Natural Science Foundation of China (61601395)

摘要

摘要: 声表面波(SAW)谐振器测量技术能在高温、高压、强电磁辐射和强电磁干扰等恶劣环境下，实现无线无源的参数检测。针对声表面波谐振器回波信号的非平稳特点，该文提出一种回波信号的频率测量方法“数字频率有效位数跟进法”(DFSPT)。仿真结果表明，该方法与现有的基于傅里叶变换法(FFT)和奇异值分解法(SVD)的方法相比，其能根据信噪比的不同，自行确定数字频率有效数字的位数，提高了频率估计的精度和稳定性。无线SAW温度传感器实验表明，该方法的频率估计标准差小，鲁棒性高。
- 声表面波 /
- 回波信号 /
- 数字频率 /
- 有效数字 /
- 频率估计
Abstract: Surface Acoustic Wave (SAW) resonator measuring technology can be used in high temperature and high pressure, strong electromagnetic radiation and strong electromagnetic interference to realize wireless passive parameter detection. Based on the the non-stationary characteristics of the SAW signal, a kind of echo signal frequency estimation method, Digital Frequency Significant Place Tracking (DFSPT) method is put forward. Compared with the existing methods based on Fast Fourier Transform (FFT) and Singular Value Decomposition (SVD), the simulation results show that the method can determine the number of significant digits of digital frequency according to the difference of signal-to-noise ratio. Thus, it can increases stability and accuracy. The experiment of wireless SAW temperature sensor shows that the frequency estimation standard deviation of this method is small and the robustness is high.
- Surface Acoustic Wave (SAW) /
- Echo signal /
- Digital frequency /
- Significant digits /
- Frequency estimation

HTML全文

图 1 不同测量距离下的回波信号时域波形

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图 2 误差图

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图 3 迭代加权前后比较图

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图 4 k值分析图

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图 5 不同信噪比下有效数字选取过程

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图 6 3种算法仿真结果

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图 7 算法耗时波动图

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图 8 测量频率值波动图

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