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High-resolution direction finding: the missing data case
Department of Electrical and Computer Engineering, University of Florida, USA.ORCID iD: 0000-0002-7599-4367
Department of Systems and Control, Uppsala University, Sweden.
2001 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 49, no 5, 950-958 p.Article in journal (Refereed) Published
Abstract [en]

This paper considers the problem of estimating the direction-of-arrival (DOA) of one or more signals using an array of sensors, where some of the sensors fail to work before the measurement is completed. Methods for estimating the array output covariance matrix are discussed. In particular, the maximum-likelihood (ML) estimate of this covariance matrix and its asymptotic accuracy are derived and discussed. Different covariance matrix estimates are used for DOA estimation together with the MUSIC algorithm and with a covariance matching technique. In contrast to MUSIC, the covariance matching technique can utilize information on the estimation accuracy of the array covariance matrix, and it is demonstrated that this yields a significant performance gain.

Place, publisher, year, edition, pages
2001. Vol. 49, no 5, 950-958 p.
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Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-77157DOI: 10.1109/78.917799OAI: oai:DiVA.org:liu-77157DiVA: diva2:525218
Available from: 2012-05-07 Created: 2012-05-07 Last updated: 2017-12-07Bibliographically approved

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Larsson, Erik G.

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