DocumentCode :
787190
Title :
Autoregressive Moving Average Spectral Estimation: A Model Equation Error Procedure
Author :
Cadzow, James A.
Author_Institution :
Department of Electrical Engineering, Virginia Polytechnic Institute, Blacksburg, VA 24061
Issue :
1
fYear :
1981
Firstpage :
24
Lastpage :
28
Abstract :
A procedure is presented for generating an autoregressive moving average (ARMA) spectral model of a stationary time series based upon a finite set of time series´ observations. The ARMA model´s autoregressive coefficients are estimated by minimizing a quadratic function of a set of basic error terms. In examples treated to date, this method has demonstrated an exceptional ability in resolving closely spaced narrow band signals in a low signal-to-noise environment where other procedures such as the maximum entropy method often fail. Its effectiveness on other classes of time series also shows promise and a more general evaluation is presently being conducted. With this in mind, the new ARMA procedure promises to be an important spectral estimation tool.
Keywords :
Autocorrelation; Autoregressive processes; Character recognition; Entropy; Equations; Fourier transforms; Frequency domain analysis; Narrowband; Signal resolution; Vehicles;
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
Publisher :
ieee
ISSN :
0196-2892
Type :
jour
DOI :
10.1109/TGRS.1981.350324
Filename :
4157200
Link To Document :
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