基于自相关的LMS自适应滤波器期望信号构建*
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陆军勤务学院

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TN911.72

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国家重点研发计划重点专项(2018YFB2003900);国家自然科学基金资助项目(61871402);重庆市研究生科研创新项目(CYS19376)


Construction of desired response of LMS adaptive filter based on autocorrelation*
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    摘要:

    针对低信噪比条件下,谱减法和频谱法构建最小均方(Least Mean Square,LMS)自适应滤波器期望信号误差大的问题,在分析LMS自适应滤波原理的基础上,提出用自相关法构建LMS自适应滤波器期望信号。首先根据噪声在不同时刻互不相关的特点,对输入信号进行采样延迟;然后为了从低信噪比环境中检测出周期信号,对延迟后信号求自相关;最后将自相关信号作为期望信号。通过仿真分析验证了该方法的有效性,可以在低信噪比条件下准确构建期望信号进行LMS自适应滤波。

    Abstract:

    Aiming at the problem that the desired response error of the least mean square (LMS) adaptive filter constructed by spectral subtraction and spectrum method was large under the condition of low signal-to-noise ratio (SNR), based on the analysis of LMS adaptive filtering principle, an autocorrelation method is proposed to construct the desired response of LMS adaptive filter. Firstly, according to the characteristic that the noise was uncorrelated at different times, the input signal was delayed; then, in order to detect the periodic signal from the low signal-to-noise ratio environment, the autocorrelation of the delayed signal was calculated; finally, the autocorrelation signal was taken as the expected response. Simulation results show that the proposed method is effective and can accurately construct the desired response for LMS adaptive filtering under the condition of low SNR.

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  • 收稿日期:2020-07-29
  • 最后修改日期:2020-08-27
  • 录用日期:2020-09-02
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