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Spectral Analysis of Periodically Gapped Data
Dept. of Electrical and Computer Engineering, University of Florida, USA.ORCID iD: 0000-0002-7599-4367
Dept. of Electrical and Computer Engineering, University of Florida, USA.
2003 (English)In: IEEE Transactions on Aerospace and Electronic Systems, ISSN 0018-9251, E-ISSN 1557-9603, Vol. 39, no 3, 1089-1097 p.Article in journal (Refereed) Published
Abstract [en]

We devise novel, interpolation-free, and computationally tractable extensions of the spectral analysis methods Capon and APES (amplitude and phase estimation) to periodically gapped data. Our methods are based on the observation that periodically gapped data usually have a structure that supports estimation of a relatively large number of covariance lags. The large signal-to-noise-ratio (SNR) behavior of the new algorithms is discussed, and numerical examples are provided to illustrate their performance.

Place, publisher, year, edition, pages
2003. Vol. 39, no 3, 1089-1097 p.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-77039DOI: 10.1109/TAES.2003.1238761OAI: oai:DiVA.org:liu-77039DiVA: diva2:524666
Available from: 2012-05-03 Created: 2012-05-03 Last updated: 2017-12-07Bibliographically approved

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Larsson, Erik G.

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