Frequency estimation of the weighted real tones or resolved multiple tones by iterative interpolation DFT algorithm

Luo, Jiufei; Xie, Zongwu; Xie, Ming

doi:10.1016/j.dsp.2015.03.002

Cited by 23 publications

(25 citation statements)

References 42 publications

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“…Then, the accuracies of the proposed procedure, L&Z&M's algorithm [11],the classical Rife's method [12] are compared through both computer simulations and experimental results. It is worth noticing that in [11] it has been shown that the L&Z&M's algorithm provides more accurate frequency estimates than previous algorithms. as a basis for comparison, the CramerRao bound (CRB) [1] is given by…”

Section: Simulation Resultsmentioning

confidence: 99%

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A Novel Frequency Estimation of Sinusoid by iterative interpolation DFT algorithm

Huang¹,

Suo²,

Shi³

2016

Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology

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Abstract. The frequency estimation of sinusoidal signal based on discrete fourier transform (DFT) is investigated, which performance is caused to decline due to the error of interpolation direction when the signal frequency is close to quantized frequency of DFT. To solve this problem, a new algorithm without weighting window is proposed. Firstly, a coarse frequency estimation in DFT spectrum is acquired, then a high-accuracy frequency near the coarse frequency by iterative interpolation is estimated. The simulation results show that errors caused by a mistaken location of the spectral line can be significantly reduced and the algorithm is simple and has good performance in mean square error and accuracy.

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Section: Simulation Resultsmentioning

confidence: 99%

“…The Kasier-Bessel and Dolph-Chebyshev windows are known for superior performance in multitone detection [10]. Frequency estimation of the weighted real tones [11].…”

Section: Introductionmentioning

confidence: 99%

A Novel Frequency Estimation of Sinusoid by iterative interpolation DFT algorithm

Huang¹,

Suo²,

Shi³

2016

Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology

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show abstract

“…The problem is more notable for the FFT of a discrete time signal, due to the picket fence effect [13,14]. The phase distortion is determined by the frequency deviation and the variation of phase response near the main lobe center of the adopted window [9].…”

Section: Phase Response Of Asymmetric Windowsmentioning

confidence: 99%

“…The phase response in the main lobe, and especially the phase response near the main lobe center is of more significance, as it has a decisive influence on the phase distortion of the tapered signal [11][12][13]. The problem is more notable for the FFT of a discrete time signal, due to the picket fence effect [13,14].…”

Section: Phase Response Of Asymmetric Windowsmentioning

confidence: 99%

Barycenter Theorem in Phase Characteristics of Symmetric and Asymmetric Windows

Luo

Zheng

et al. 2018

Symmetry

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Asymmetric windows are of increasing interest to researchers because of the nonlinear and adjustable phase response, as well as alterable time delay. Short-time phase distortion can provide an essential improvement in speech coding, and also has better performance in speech recognition. The merits of asymmetric windows in the aspect of spectral behaviors have an important function in frequency component detection and parameter estimation. In this paper, the phase response of windows were further studied, and the phase characteristics of symmetric and asymmetric windows are described. The relationship between the barycenter of windows in the time domain, and the phase characteristic at the center of the main lobe in the frequency domain, was established. In light of the relationship, an improved version of the asymmetric window-based frequency estimation algorithm was proposed. The improved algorithm has advantages of straightforward implementation and computational efficiency. The numeric simulation results also indicate that the improved approach is more robust than the traditional method against additive random noise.

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“…The essence of this method is to obtain the frequency estimate of a signal with the weighted average of a certain number of known spectral bins [6][7][8]. When a maximum sidelobe decay window is selected, the frequency can be estimated by means of simple analytical relationships.…”

mentioning

confidence: 99%

Frequency Estimation of Weighted Signals Based On DFT Interpolation Algorithm

Xie¹

2017

Proceedings of the 3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016)

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Abstract-It is generally demanded for strict frequency estimation of sinusoidal signal in a good many engineering practice situations. This paper puts forward an iterative frequency estimation algorithm on strength of the interpolation of Fourier coefficients of weighted samples. The algorithm is practically believed to be almost applicative for all regular window functions. Systematic errors of a variety of windows are given in this paper, and the proposed algorithm's performance is examined and verified with occurrence of white Gaussian noise. The outcomes of simulation identify that it could be significantly lessened for errors touched off by the mistaken location of spectral line. It is direct and candid to implement the proposed algorithm with high precision, benign compatibility and favorable robustness to additive noise, which altogether endow it a perfect algorithm to strictly estimate the frequency of spectral analysis.

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Frequency estimation of the weighted real tones or resolved multiple tones by iterative interpolation DFT algorithm

Cited by 23 publications

References 42 publications

A Novel Frequency Estimation of Sinusoid by iterative interpolation DFT algorithm

A Novel Frequency Estimation of Sinusoid by iterative interpolation DFT algorithm

Barycenter Theorem in Phase Characteristics of Symmetric and Asymmetric Windows

Frequency Estimation of Weighted Signals Based On DFT Interpolation Algorithm

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