相减策略的实复转换式参数估计算法

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摘要为抑制实信号中负频率成分对参数估计的影响，提高参数估计精度，提出一种相减策略的实复转换式参数估计算法。利用FFT算法对采样信号进行预处理，构造只含有负频率成分的参考信号；采用相减策略将采样信号和参考信号相减以实现实复转换；对生成的复信号进行频谱插值分析，得到频率偏移量估计值；经迭代计算得到精确的频率、幅值和初相位估计值。同时，通过构造参考信号，并根据相减策略和信噪比的定义求解采样信号的信噪比。仿真实验结果表明：所提算法抑制了负频率成分的影响，在不同信噪比、不同频率条件下均具有良好的频率估计精度，频率估计的均方误差更接近于克拉美罗下限，并且具有良好的幅值、初相位和信噪比估计性能。

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	陈鹏
	涂亚庆
	刘言
	李明
	牟泽龙

关键词 ：参数估计, 相减策略, 实复转换

Abstract：To suppress the influence of negative frequency component of a real signal on its parametric estimation, and improve the accuracy of parametric estimation, a real-complex conversion parametric estimation algorithm based on the subtraction strategy was proposed.Firstly, the sample signal was pre-processed with FFT algorithm to construct the reference signal only containing negative frequency components.Secondly, the subtraction strategy was used to subtract the reference signal from the sample one to realize the real-complex conversion.Then, the spectral interpolation analysis was done for the generated complex signal to obtain the estimated value of frequency offset.Finally, accurate estimated values of frequency, amplitude and initial phase were obtained with iterative calculation.Meanwhile, the estimated value for the signal to noise ratio (SNR) of the sample signal was solved through constructing the reference signal and using definitions of the subtraction strategy and SNR.The simulation test results indicated that the proposed algorithm can suppress the influence of negative frequency components, and have a good frequency estimation accuracy under conditions of different SNRs and frequencies, the mean square error of the frequency estimation value is closer to Cramer-Rao lower bound; it has good estimation performances for amplitude, initial phase and SNR of signals.

Key words： parametric estimation subtraction strategy real-complex conversion

收稿日期: 2019-09-24 出版日期: 2020-10-28

引用本文:

陈鹏,涂亚庆,刘言,李明,牟泽龙. 相减策略的实复转换式参数估计算法[J]. 振动与冲击, 2020, 39(21): 211-216.
CHEN Peng, TU Yaqing, LIU Yan, LI Ming, MOU Zelong. Real-complex conversion parametric estimation algorithm based on subtraction strategy. JOURNAL OF VIBRATION AND SHOCK, 2020, 39(21): 211-216.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2020/V39/I21/211

[1] 陈鹏, 涂亚庆, 李明, 等. 基于迭代插值的实复转换频率估计算法[J]. 振动与冲击, 2019, 38(18): 35-39.
CHEN Peng, TU Yaqing, LI Ming, et al. Real-to-complex-transformation frequency estimation algorithm based on iterative interpolation [J]. Journal of Vibration and Shock, 2019, 38(18): 35-39.
[2] 沈廷鳌, 涂亚庆, 张海涛, 等. 一种改进的自适应格型陷波频率估计算法及其收敛性分析[J]. 振动与冲击, 2013, 32(24):28-32.
SHEN Ting-ao, TU Yaqing, ZHANG Haitao, et al. A modified frequency estimation method of adaptive lattice notch filter and its convergence analysis [J]. Journal of Vibration and Shock, 2013, 32(24):28-32.
[3] Duda K, Magalas L B, Majewski M, et al. DFT-based estimation of damped oscillation parameters in low-frequency mechanical spectroscopy [J]. IEEE Transactions on Instrumentation & Measurement, 2011, 60(11):3608-3618.
[4] Tu Y Q, Shen Y L. Phase correction autocorrelation-based frequency estimation method for sinusoidal signal [J]. Signal Processing, 2017, 130:183-189.
[5] Cao Y, Wei G, Chen F J. A closed-form expanded autocorrelation method for frequency estimation of a sinusoid [J]. Signal Processing, 2012, 92(4):885-892.
[6] Tu Y Q, Shen Y L, Zhang H T, et al. Phase and frequency matching-based signal processing method for Coriolis mass flowmeters[J]. Measurement Science Review, 2016, 16(2):62-67.
[7] Kenefic R J, Nuttall A H. Maximum likelihood estimation of the parameters of a tone using real discrete data [J]. Oceanic Engineering IEEE Journal of, 1987, 12(1):279-280.
[8] Aboutanios E, Mulgrew B. Iterative frequency estimation by interpolation on Fourier coefficients [J]. IEEE Transactions on Signal Processing, 2005, 53(4): 1237-1242.
[9] Duda K and Barczentewicz S. Interpolated DFT for sinα(x) windows [J]. IEEE Transactions Instrument and Measurement, 2014, 63(4): 754–760.
[10] Djukanović S. An accurate method for frequency estimation of a real sinusoid [J]. IEEE Signal Processing Letters, 2016, 23(7):915-918.
[11] CHEN P, TU Y Q, LI M, et al. A real-to-complex conversion phase difference estimation method for Coriolis mass flowmeter signal [C]. 2019 International Conference on Communications, Information System and Computer Engineering (CISCE), Nanjing, 2019: 280-284.
[12] 李思超, 叶甜春, 徐建华. 通信系统仿真中估计正弦信号信噪比的新方法[J]. 电子测量技术, 2009, 34(3): 56-59.
LI Sichao, YE Tianchun, XU Jianhua. Novel method for estimating SNR of sine signal in communication system simulation [J]. Electronic Measurement Technology, 2009, 34(3): 56-59.
[13] Tankizawa K, Sasaki S, Zhou J, et al. Online SNR estimation for parallel combinatorial ss systems in Nakagami Fading Channels [C]. Pro. Of GLOBE-COM’02, Taipei, Taiwan, 2002: 1239-1243.
[14] 许爱强, 魏辉, 汪定国, 等. 基于Matlab估计正弦信号信噪比时频法研究[J]. 测试技术学报, 2012, 26(1): 46-50.
XU Aiguo, WEI Hui, WANG Dingguo, et al. Research on time-frequency method for estimating SNR of sine signal based on Matlab [J]. Journal of Test and Measurement Technology, 2012, 26(1): 46-50.
[15] Kay S M. Fundamentals of Statistical Signal Processing, Volume III (Paperback) [J]. Detection Theory, 1993, 37(4):465-466.
[16] Vucijak N M, Saranovac L V. A simple algorithm for the estimation of phase difference between two sinusoidal voltages [J]. IEEE Transactions on Instrumentation and Measurement, 2010, 59(12):3152-3158.
[17] Shen Y L and Tu Y Q. Correlation theory-based signal processing method for CMF signals [J]. Measurement Science and Technology, 2016, 27(6): 065006.