Parameter estimation of exponentially damped sinusoids based on state-space model

被引：0
|
作者：
Yu X.-H. [1 ]
Zhang Z.-C. [2 ]
Li X.-B. [1 ]
Sun X.-D. [1 ]
机构：
[1] College of Communication Engineering, Jilin University, Changchun
[2] School of Automation, Beijing University of Posts and Telecommunications, Beijing
来源：
Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition) | 2019年 / 49卷 / 06期
关键词：
Attenuation factor estimation; Exponentially damped sinusoids; Frequency estimation; Information processing technology; State-space model;
D O I：
10.13229/j.cnki.jdxbgxb20181028
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
A state-space model method was proposed for the joint estimation of attenuation factor and frequency of multi-component exponentially damped sinusoids. Firstly, a state-space model which includes the system matrix was established, and the system matrix was comprised of the information of estimated attenuation factor and frequency. Secondly, by solving the state-space model equation, the estimated value of generalized observable matrix was derived. Finally, based on the generalized observable matrix, the estimated values of the system matrix were obtained, which were further used to estimate the attenuation factor and frequency. The algorithm has the advantages of low computation complexity and automatic matching in parameters. The simulations show that the state-space model algorithm is superior to ESPRIT algorithm in low SNR. © 2019, Jilin University Press. All right reserved.
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页码：2083 / 2088
页数：5
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  • [1] Yem V., Kajimoto H., Combination of cathodic electrical stimulation and mechanical damped sinusoidal vibration to express tactile softness in the tapping process, Haptics Symposium, pp. 84-88, (2018)
  • [2] Tomar S., Sumathi P., Amplitude and frequency estimation of exponentially decaying sinusoids, IEEE Transactions on Instrumentation and Measurement, 67, 1, pp. 229-237, (2018)
  • [3] Quinn B.G., Estimating parameters in noisy low frequency exponentially damped sinusoids and exponentials, International Conference on Acoustics, Speech and Signal Processing, pp. 4298-4302, (2016)
  • [4] Umesh S., Tufts D.W., Estimation of parameters of exponentially damped sinusoids using fast maximum likelihood estimation with application to NMR spectroscopy data, IEEE Transactions on Signal Processing, 44, 9, pp. 2245-2259, (2002)
  • [5] Wang Y., Chen B., Pin G., Et al., Estimation of damped sinusoidal signals: an observer-based approach, 50, 1, pp. 3811-3816, (2017)
  • [6] Xiao X., Lai J.H., Wang C.D., Parameter estimation of the exponentially damped sinusoids signal using a specific neural network, Neurocomputing, 143, 143, pp. 331-338, (2014)
  • [7] Nouri Z., Mojiri M., Zekri M., Estimation of damped oscilations using adaline network, 201523rd Iranian Conference on Electrical Engineering, pp. 939-944, (2015)
  • [8] Najy W.K.A., Zeineldin H.H., Alaboudy A.H.K., Et al., A Bayesian passive islanding detection method for inverter-based distributed generation using ESPRIT, IEEE Transactions on Power Delivery, 26, 4, pp. 2687-2696, (2011)
  • [9] Tian B.-F., Zhu H., Yi X.-F., Et al., Denoising and extraction method of magnetic resonance sounding signal based on adaptive harmonic modeling and autocorrelation, Chinese Journal of Geophysics, 61, 2, pp. 767-780, (2018)
  • [10] Wang Y.-Q., Yuan S.-J., Ma B.-L., New estimation method for damped exponential model parameters, Radio Engineering, 42, 12, pp. 26-29, (2012)
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