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Modified IQML and a Statistically Efficient Method for Direction Estimation without Eigendecomposition
KTH, Superseded Departments, Signals, Sensors and Systems.
KTH, Superseded Departments, Signals, Sensors and Systems.ORCID iD: 0000-0002-6855-5868
KTH, Superseded Departments, Signals, Sensors and Systems.ORCID iD: 0000-0003-2298-6774
1998 (English)In: Proceedings IEEE International Conference on Acoustics, Speech, and Signal Processing, IEEE , 1998, 2069-2072 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper deals with direction estimation of signals impinging on a uniform linear sensor array. A well known algorithm for this problem is iterative quadratic maximum likelihood (IQML). Unfortunately, the IQML estimates are in general biased, especially in noisy scenarios. We propose a modification of IQML (MIQML) that gives consistent estimates at approximately the same computational cost. In addition, an algorithm with an estimation error covariance which is asymptotically identical to the asymptotic Cramer-Rao lower bound is presented. The optimal algorithm resembles weighted subspace fitting or MODE, but achieves optimal performance without having to compute an eigendecomposition of the sample covariance matrix.

Place, publisher, year, edition, pages
IEEE , 1998. 2069-2072 p.
Keyword [en]
Costs, Covariance matrix, Data models, Direction of arrival estimation, Iterative algorithms, Maximum likelihood estimation, Sensor arrays, Sensor systems, Time sharing computer systems, Vectors
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-86457DOI: 10.1109/ICASSP.1998.681551OAI: oai:DiVA.org:kth-86457DiVA: diva2:500725
Conference
IEEE International Conference on Acoustics, Speech, and Signal Processing(ICASSP), Seattle, WA, USA, May 1998
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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Output format
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