ARMA spectral estimation of narrow-band processes via model reduction
1990 (English)In: IEEE Transactions on Acoustics, Speech, and Signal Processing, ISSN 0096-3518, Vol. 38, no 7, 1144-1154 p.Article in journal (Refereed) Published
The problem of estimating autoregressive moving average (ARMA) models for narrowband processes is considered. The following approach is proposed. Estimate a high-order autoregressive (AR) approximation of the process. By model reduction, based on a truncated internally balanced realization or optimal Hankel-norm model reduction, reduce the order of this high-order AR estimate to find a lower-order ARMA model. This algorithm gives ARMA spectral estimates with excellent resolution properties, without using iterative numerical minimization methods as for the maximum-likelihood method. How to take the narrowband assumption into account in the model reduction step is discussed in detail.
Place, publisher, year, edition, pages
1990. Vol. 38, no 7, 1144-1154 p.
Computer Programming--Algorithms, Statistical Methods--Time Series Analysis, ARMA Processes, Autoregressive Moving Average Processes, Model Reduction, Narrowband Processes, Spectral Estimation, Spectrum Analysis
IdentifiersURN: urn:nbn:se:kth:diva-55446DOI: 10.1109/29.57543ISI: A1990DK88900008OAI: oai:DiVA.org:kth-55446DiVA: diva2:471573
QC 20120104. Correspondence Address: Wahlberg, Bo; Dep of Electr Eng, Linkoping Univ,, Linkoping, Swed2012-01-022012-01-022016-05-27Bibliographically approved