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Analysis of a Subspace-based Spatial Frequency Estimator
KTH, Superseded Departments, Signals, Sensors and Systems.ORCID iD: 0000-0002-6855-5868
KTH, Superseded Departments, Signals, Sensors and Systems.
KTH, Superseded Departments, Signals, Sensors and Systems.ORCID iD: 0000-0003-2298-6774
1997 (English)In: Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP-97), 1997, 4001-4004 p.Conference paper, Published paper (Refereed)
Abstract [en]

In a previous paper we presented a novel method for spatial and temporal frequency estimation assuming that the sources are uncorrelated. The current paper analyzes this method in the case of spatial frequency estimation. In particular an optimal weighting matrix is derived and it is shown that the asymptotic variance of the frequency estimates coincides with the relevant Cramer-Rao lower bound. This means that the estimator is in large samples an efficient subspace-based spatial frequency estimator. The proposed method thus utilizes the a priori knowledge about the signal correlation as opposed to previously known subspace estimators. Moreover, when a uniform linear array is employed, it is possible to implement the estimator in a non-iterative fashion.

Place, publisher, year, edition, pages
1997. 4001-4004 p.
Keyword [en]
Additive white noise, Algorithm design and analysis, Covariance matrix, Direction of arrival estimation, Eigenvalues and eigenfunctions, Frequency estimation, Performance analysis, Sensor arrays, Sensor systems, Wavelength measurement
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-86503DOI: 10.1109/ICASSP.1997.604813OAI: oai:DiVA.org:kth-86503DiVA: diva2:500775
Conference
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP-97), München, Germany, Apr. 1997
Note
NR 20140805Available from: 2012-02-13 Created: 2012-02-13 Last updated: 2012-02-13Bibliographically approved

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Jansson, MagnusOttersten, Björn

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  • apa
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Output format
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  • asciidoc
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