Autocorrelation model-based identification method for ARMA systems in noise

被引：11

作者：

Hasan, MK ^{[1
]}

Hossain, NM

Naylor, PA

机构：

[1] Univ London Imperial Coll Sci Technol & Med, Commun & Signal Proc Grp, Dept Elect & Elect Engn, London SW7 2AZ, England

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

来源：

IEE PROCEEDINGS-VISION IMAGE AND SIGNAL PROCESSING | 2005年 / 152卷 / 05期

关键词：

D O I：

10.1049/ip-vis:20045042

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：

A novel method for parameter estimation of minimum-phase autoregressive moving average (ARMA) systems in noise is presented. The ARMA parameters are estimated using a damped sinusoidal model representation of the autocorrelation function of the noise-free ARMA signal. The AR parameters are obtained directly from the estimates of the damped sinusoidal model parameters with guaranteed stability. The MA parameters are estimated using a correlation matching technique. The simulation results show that the proposed method can estimate the ARMA parameters with better accuracy as compared to other reported methods, in particular for low SNRs.

引用

页码：520 / 526

页数：7

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