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Frequency estimation of discrete time signals based on fast iterative algorithm

机译:基于快速迭代算法的离散时间信号频率估计

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摘要

A fast iterative algorithm for frequency estimation is developed in this paper to improve the frequency tracking performance. If the signal is transformed by a mathematical tool, the signal to noise ratio (SNR) should not be greatly reduced after the transformation. The analysis presented in this paper showed that the traditional method for frequency estimation causes large noise at high frequency range, therefore, the suitable estimation range of traditional method is only from 0 to fs/6 Hz (fs is the sample frequency). In order to overcome this limitation, a new structure of iterative algorithm is established to extend the upper bound frequency from fs/6 to fs/2 Hz. The experimental noisy sinusoid signal frequency estimation and chirp signal frequency tracking confirmed that the novel algorithm showed improved performance. Furthermore, the average estimation error was decreased over 30% (under SNR = 15 dB) when applying the novel iterative algorithm. The novel iterative algorithm will have broad applications in fields of signal processing and communication systems. (C) 2016 Elsevier Ltd. All rights reserved.
机译:为了提高频率跟踪性能,本文提出了一种快速迭代的频率估计算法。如果通过数学工具对信号进行了转换,则转换后不应大幅降低信噪比(SNR)。本文的分析表明,传统的频率估计方法在高频范围内会产生较大的噪声,因此,传统方法的合适估计范围仅为0到fs / 6 Hz(fs是采样频率)。为了克服此限制,建立了一种新的迭代算法结构,以将上限频率从fs / 6 Hz扩展到fs / 2 Hz。实验性的噪声正弦信号频率估计和线性调频信号频率跟踪证实了该新算法具有改进的性能。此外,当应用新颖的迭代算法时,平均估计误差降低了30%以上(在SNR = 15 dB下)。该新颖的迭代算法将在信号处理和通信系统领域中具有广泛的应用。 (C)2016 Elsevier Ltd.保留所有权利。

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