计算机与现代化

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基于延时互相关的正弦信号频率估计方法

  

  1. (陆军勤务学院,重庆401311)
  • 收稿日期:2018-06-13 出版日期:2018-09-29 发布日期:2018-09-30
  • 作者简介:闫隆基(1994-),男,黑龙江庆安人,陆军勤务学院硕士研究生,研究方向:智能检测与智能控制; 通信作者:肖玮(1982-),女,重庆人,讲师,硕士生导师,博士,研究方向:信号处理与物联网工程; 陈鹏(1992-),男,重庆人,博士研究生,研究方向:数字信号处理。
  • 基金资助:
    国家自然科学基金资助项目(61302175, 61271449, 61871402); 重庆市自然科学重点基金资助项目(CSTC2015-jcyjBX0017)

Sinusoidal Signal Frequency Estimation Method Based on Delay Cross-correlation

  1. (Army Logistical Engineering University of PLA, Chongqing 401311, China)
  • Received:2018-06-13 Online:2018-09-29 Published:2018-09-30

摘要: 为提高非整周期采样信号的频率估计精度,提出一种基于延时互相关的正弦信号频率估计方法。首先,截取一段采样信号及其等长度延时信号;其次,对2段信号做互相关运算,并构建不包含误差项的误差校正信号;然后,对误差校正信号进行频率粗估计,并生成参考信号;最后,根据柯西-施瓦兹不等式构造误差函数,通过最小化误差函数得到频率精估计值。仿真实验结果表明:该方法能有效降低非整周期采样的影响,提高频率估计精度,其估计精度优于同等条件下基于自相关的频率估计方法,使得频率估计值的均方误差更接近克拉美罗下限。

关键词: 频率估计, 延时互相关, 非整周期采样, 正弦信号, 误差校正

Abstract: To improve the frequency estimation precision of the sampled signals with non-integer period, a frequency estimation method for sinusoidal signal based on delay cross-correlation is proposed. Firstly, the sampled signal and its equal length delay signal are truncated. Secondly, the two segment signals are calculated by cross-correlation, and the error correction signal with non error term is constructed. Then, the coarse frequency estimation of the error correction signal is obtained, and the reference signal is generated. Finally, the error function is constructed according to the Cauchy Schwarz inequality, and the fine frequency estimation value is obtained by minimizing the error function. The results of simulation experiments indicate that the proposed method effectively reduces the influence of the non-integer period sampling, and improves the accuracy of frequency estimation, which is better than the frequency estimation method based on autocorrelation under the same conditions. The root mean square errors of the frequency estimation value are closer to the Cramer-Rao lower bound.

Key words: frequency estimation, delay cross-correlation, non-integer period sampling, sinusoidal signal, error correction

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