Modified IQML and a Statistically Efficient Method for Direction Estimation without Eigendecomposition
1998 (English)In: Proceedings IEEE International Conference on Acoustics, Speech, and Signal Processing, IEEE , 1998, 2069-2072 p.Conference paper (Refereed)
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.
Costs, Covariance matrix, Data models, Direction of arrival estimation, Iterative algorithms, Maximum likelihood estimation, Sensor arrays, Sensor systems, Time sharing computer systems, Vectors
IdentifiersURN: urn:nbn:se:kth:diva-86457DOI: 10.1109/ICASSP.1998.681551OAI: oai:DiVA.org:kth-86457DiVA: diva2:500725
IEEE International Conference on Acoustics, Speech, and Signal Processing(ICASSP), Seattle, WA, USA, May 1998
NR 201408052012-02-132012-02-132012-02-13Bibliographically approved