基于离散傅里叶变换和最小二乘的频率估计

Zhang Gang-bing, Liu Yu, Xu Jia-jia, Hu Guo-bing
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引用次数: 6

摘要

提出了一种正弦信号的频率估计算法。它由粗频率估计和细频率估计组成。离散傅里叶变换(DFT)决定了粗频估计,最小二乘估计(LSE)使得到最优频差估计成为可能。随后,我们推导了渐近误差方差(AEV)与Cramer-Rao界(CRB)之间的关系。仿真结果表明,当信噪比(SNR)大于阈值时,该算法的性能接近正弦波的CRB。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Frequency estimation based on discrete Fourier transform and least squares
A frequency estimation algorithm of sinusoidal signal was presented. It consists of a coarse frequency estimation followed by fine frequency estimation. Discrete Fourier transform (DFT) determines the coarse frequency estimation and least squares estimator (LSE) makes it possible to get the optimal frequency difference estimation. Subsequently, we derive the relationship between the asymptotic error variance (AEV) and the Cramer-Rao bound (CRB). Simulation results show that the performance of the proposed algorithm approaches the CRB of the sinusoid when the signal-to-noise ratio (SNR) is higher than the SNR threshold.
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