Identification of noisy AR systems using damped sinusoidal model of autocorrelation function

被引：14

作者：

Hasan, MK ^{[1
]}

Fattah, SA ^{[1
]}

Khan, MR ^{[1
]}

机构：

[1] Bangladesh Univ Engn & Technol, Dept Elect & Elect Engn, Dhaka 1000, Bangladesh

来源：

IEEE SIGNAL PROCESSING LETTERS | 2003年 / 10卷 / 06期

关键词：

aautoregressive (AR) parameter estimation; damped sinusoidal modeling; low signal-to-noise ratio (SNR);

D O I：

10.1109/LSP.2003.811590

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This letter presents a novel method for minimumphase autoregressive (AR) system identification at a very low SNR using damped sinusoidal model representation of the autocorrelation function of the noise-free AR signal with guaranteed stability. The new model parameters are estimated solely from the given noisy observations. Then AR parameters are obtained directly from the estimates of the damped sinusoidal model parameters. The simulation results show that the proposed method can estimate the AR system parameters with high accuracy even at an SNR as low as -5 dB.

引用

页码：157 / 160

页数：4

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