一种新的正弦信号频率估计自相关方法

Chao H. Huang, Jidong Suo, T. Liu
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引用次数: 1

摘要

基于正弦信号的线性预测特性,提出了一种针对高斯白噪声中单音正弦信号的自相关方法。首先,推导了一种新的封闭自相关表达式,它比传统的自相关表达式对频率估计的贡献更大;然后,受RIM估计器的启发,我们提出了一种新的利用多个自相关滞后的估计器。计算机仿真结果表明,与几种基于自相关的估计方法相比,该方法在较低信噪比下精度更接近于Cramer-Rao界(CRB),并且具有较低的计算复杂度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A novel autocorrelation approach for frequency estimation of a sinusoid
Based on the linear prediction (LP) property of sinusoidal signals, a novel autocorrelation approach for a single-tone sinusoidal signal emerged in Gaussian white noise is proposed. Firstly, a new closed-form autocorrelation expression is derived that it contributes more to frequency estimation than conventional autocorrelation expressions, then, inspired by RIM estimator, we propose a novel estimator using multiple autocorrelation lags. Computer simulations show that the accuracy of the proposed approach is closer to the Cramer-Rao bound(CRB) especially for lower signal noise radio(SNR) and has lower computation complexity via comparing with several autocorrelation-based estimators.
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