An empirical investigation of the properties of the autoregressive spectral estimator

M. Kaveh, G. R. Cooper

Research output: Contribution to journalArticlepeer-review

Abstract

The autoregressive (AR) spectral estimator is used to make high resolution spectral estimates based on short data records. Measures of a frequency averaged normalized bias and normalized variance of the spectral estimates are introduced. A large number of spectra are generated. Based on the above mentioned measures and visual inspection of the estimates of the generated spectra, the AR and the conventional tapered and transformed (TT) spectral estimates are compared. It is shown that the AR spectral estimator is as stable as that given by its asymptotic variance. It is also shown that the AR spectral estimator is most powerful in estimating narrow spectral peaks with a high signal to interference ratio in the signal bandwidth.

Original languageEnglish (US)
Pages (from-to)313-323
Number of pages11
JournalIEEE Transactions on Information Theory
Volume22
Issue number3
DOIs
StatePublished - 1976
Externally publishedYes

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