A frequency estimation algorithm based on spectrum correlation of multi-section sinusoids with known frequency-difference

被引：0

作者：

Xiao, Wei ^{[1
]}

Tu, Ya-Qing ^{[1
]}

Liu, Liang-Bing ^{[1
]}

Mo, Zheng-Jun ^{[1
]}

Mao, Yu-Wen ^{[1
]}

机构：

[1] Logistical Engineering University

来源：

Yuhang Xuebao/Journal of Astronautics | 2012年 / 33卷 / 08期

关键词：

Frequency estimation; Multi-sinusoids with the Known Frequency-Difference (M-Sinusoids-KFD); Signal processing; Spectrum correlation;

D O I：

10.3873/j.issn.1000-1328.2012.08.022

中图分类号：

TN911 [通信理论];

学科分类号：

081002 ;

摘要：

Based on spectrum correlation of Multi-section sinusoids with Known Frequency-Difference (M-sinusoids-KFD), a frequency estimation algorithm is proposed to improve frequency estimation accuracy of the short sinusoid in low SNR and to extend the applicable range of the multi-section signal fusion method. To deal with the spectrum problems caused by the known frequency-difference and to make the spectrum of M-sinusoids-KFD as same as the multi-section co-frequency sinusoids, the frequency-difference correction matrix is created. Then, through weighted-accumulation spectrum of M-Sinusoids-KFD by the designed weighted factor, the gained optimization weighted-accumulation spectra become approximately the same as a coherent phase sinusoid. To suppress the false spectral peak and noises, the correlation spectrum is constructed by correlating the optimization weighted-accumulation spectrum and the accumulated spectrum of M-Sinusoids-KFD. Finally, accurate frequency estimation can be obtained through spectral peak searching of the correlation spectrum. Simulation results demonstrate that the proposed algorithm works better in accuracy, noise immunity and universality, especially has a superior performance for the short sinusoid in low SNR compared with some present algorithms.

引用

页码：1150 / 1157

页数：7

共 14 条

[1]

Vizireanu D.N., A simple and precise real-time four point single sinusoid signals instantaneous frequency estimation method for portable DSP based instrumentation, Measurement, 44, 2, pp. 500-502, (2011)

[2]

So H.C., Chan F.K.W., Sun W., Subspace approach for fast and accurate single-tone frequency estimation, IEEE Trans. on Signal Processing, 59, 2, pp. 827-831, (2011)

[3]

Liu C., Skafidas E., Evans R., Capacity and data rate for millimeter wavelength systems in a short range package radio transceiver, IEEE Trans. On Wireless Comm., 9, 3, pp. 903-906, (2010)

[4]

Prioakis J.G., Manolakis D.G., Digital Signal Processing: Principle, Algorithms, and Application, pp. 112-114, (2006)

[5]

Meng J., Phase association method of multisection sampled data, Systems Engineering and Electronics, 26, 12, pp. 1784-1786, (2004)

[6]

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, 1, pp. 194-198, (2009)

[7]

Seunghwan L., Yonghwan L., Adaptive frequency hopping and power control based on spectrum characteristic of error sources in Bluetooth systems, Computers & Electrical Engineering, 36, 2, pp. 341-351, (2010)

[8]

Assous S., Hopper C., Lovell M.A., Et al., Short pulse multi-frequency phase-based time delay estimation, Journal of the Acoustical Society of America, 127, 1, pp. 309-315, (2010)

[9]

Xiao W., Tu Y.Q., Liu L.B., Parameters estimation of LFM signal based on fusion of signals with the same length and known frequency-difference, IEEE Proceedings of the 8th World Congress on Intelligent Control and Automation, pp. 6776-6781, (2010)

[10]

Qiufen Y., Weihua G., Huosheng H., A novel information fusion based FTT algorithm for a driver fatigue monitoring system, International Journal of Modelling, Identification and Control, 10, 3, pp. 230-237, (2010)

← 1 2 →