Title

Weighted subspace fitting using subspace perturbation expansions

Document Type

Conference Proceeding

Date of Original Version

12-1-1998

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. © 1998 IEEE.

Publication Title

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volume

4

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