Frequency Estimation Algorithms by Fusion Spectra of Multi-section Sinusoids

• Autorzy: Xiao W. , Tu Y. , Liu L. , Shen Y. , Zhang L.

Warianty tytułu

PL

Estymacja częstotliwości z wykorzystaniem widma fuzji M-częstotliwości sinusoid

• Języki publikacji: EN

Abstrakty

EN

For achieving a more precise frequency estimation of a short sinusoid at low SNR, a algorithm based on fusion spectra of Multi-section Sinusoids(M-sinusoids) was proposed. In order to solve the discontinuous phases problem of M-sinusoids, the Optimization Weighted-Accumulation (OW-A) spectrum was gained through weighted-accumulation spectra of M-sinusoids by the designed weighted factor. The correlation spectrum, which could inherit the narrow and high main-lobe of the OW-A spectrum, and the good noise immunity of the accumulation spectrum of M-sinusoids, was constructed by correlation OW-A spectrum and the accumulation spectrum. Therefore, higher precision frequency estimation could be obtained through spectral peak searching of the correlation spectrum. Moreover, in order to meet the high real-time demand in some fields, a fast algorithm of the proposed algorithm was put forward. This fast algorithm could reduce most computational cost of the proposed algorithm by the following techniques: design a fast DTFT algorithm, reduction dimensions of the weighted fusion spectrum matrix, 1/3 main-lodes correlation of the OW-A spectrum and the accumulation spectrum. Simulations demonstrate the superior performance of the proposed algorithms; the fast algorithm could reduce most calculation of the proposed algorithm with lowering a little frequency estimation precision, and it works better in very low SNR (SNR≤-13dB).

PL

W artykule zaproponowano algorytm estymacji częstotliwości krótkich fal sinusoidalnych o niskim zaszumieniu (SNR). Rozwiązanie bazuje na widmie fuzji M-częstotliowości sinusoid (M-sinusoids). W celu rozwiązania problemu nieciągłości faz M-sinusoid zastosowano współczynniki wagowe zawartości częstotliwości, co pozwoliło na ich optymalizację (ang. Optimization Weighted-Accumulation). Zastosowanie algorytmu pozwala na zwiększenie precyzji estymacji przy jednoczesnym zwiększeniu szybkości wykonania. Wyniki badań symulacyjnych potwierdzają skuteczność działania.

Słowa kluczowe

EN

frequency estimation; spectra fusion; multi-section sinusoids; m-sinusoids; signal processing

PL

estymacja częstotliwości; widmo fuzji; multiczęstotliwość sinusoid; przetwarzanie sygnału

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2013
• Tom: R. 89, nr 3b
• Strony: 246--253
• Opis fizyczny: Bibliogr. 12 poz., schem., tab., wykr.

Twórcy

autor

Xiao W.

• Department of Logistical Information Engineering, Logistical Engineering University,Chongqing,China

autor

Tu Y.

• Department of Logistical Information Engineering, Logistical Engineering University,Chongqing,China

autor

Liu L.

• Department of Logistical Information Engineering, Logistical Engineering University,Chongqing,China

autor

Shen Y.

• Department of Logistical Information Engineering, Logistical Engineering University,Chongqing,China

autor

Zhang L.

• Zhuozhou Comprehensive Storehouse,Hebei, China

Bibliografia

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• [2] Candan C., A method for fine resolution frequency estimation from three DFT samples. IEEE SPL,18(2011), No.6, 351-354.
• [3] Chan F., So H. C., Lau W. H., Chan C. F., Efficient approach for sinusoidal frequency estimation of gapped data, IEEE Signal Processing Letters, 17(2010), No.6, 611-614.
• [4] Prioakis J. G., Manolakis D. G., Digital signal processing: principle, algorithms, and application, New Jersey: Prentice Hall, 2006:112-114.
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• [6] Ju P. H., Qin S. R., Qin Y., Ding Z. Y., Research on earlier fault diagnosis of gear by method of multi-resolution empirical mode decomposition and frequency domain averaging. PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 89 NR 3b/2013 253
• [7] Journal of Vibration and Shock, 28(2009), No.5, 97-101.
• [8] Zhang H. T., Tu Y. Q., New signal processing method with negative frequency contribution for Coriolismass flowmeter, Chinese Journal of Scientific Instrument, 28(2007), No.3, 539-544.
• [9] Bluestein L. I., A linear filtering approach to the computation of the discrete Fourier transform, IEEE Transactions on Audio and Electroacoustics, 18(1970), No.4, 451-455.
• [10] Zhao X. Q., Guo Y. C., DSP implementation and blind equalization algorithms based on coordinate transformation, 2010 2nd International Asia Conference on Informatics in Control, Automation and Robotics, Wuhan, China, March 6 - 7, (2010), 79-82.
• [11] Liu L. B., Tu Y. Q., Zhang H. T., Fusion algorithm for frequency estimation of multi-section signals with same frequency and length, Journal of System Simulation, 21(2009), No.1, 194-198.
• [12] Ding K., Zhu W. Y., Yang Z. J., Li W. H., Parameter estimation accuracy of FFT and FT discrete spectrum correction, Journal of Mechanical Engineering, 46(2010), No.7,48-73.