DocumentCode
2087073
Title
Weighted subspace fitting using subspace perturbation expansions
Author
Vaccaro, Richard J.
Author_Institution
Dept. of Electr. Eng., Rhode Island Univ., Kingston, RI, USA
Volume
4
fYear
1998
fDate
12-15 May 1998
Firstpage
1973
Abstract
This paper presents a new approach to deriving statistically optimal weights for weighted subspace fitting (WSF) algorithms. The approach uses a formula called a “subspace perturbation expansion,” which shows how the subspaces of a matrix change when the matrix elements are perturbed. The perturbation expansion is used to derive an optimal WSF algorithm for estimating directions of arrival in array signal processing
Keywords
array signal processing; direction-of-arrival estimation; matrix algebra; optimisation; statistical analysis; DOA; array signal processing; directions of arrival; matrix elements; optimal WSF algorithm; statistically optimal weights; subspace perturbation expansions; weighted subspace fitting algorithms; Array signal processing; Cost function; Data mining; Direction of arrival estimation; Matrix decomposition; Parameter estimation; Signal processing; Signal processing algorithms; Singular value decomposition; System identification;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on
Conference_Location
Seattle, WA
ISSN
1520-6149
Print_ISBN
0-7803-4428-6
Type
conf
DOI
10.1109/ICASSP.1998.681451
Filename
681451
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