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Proceedings Paper

Adaptive beamforming using recursive eigenstructure updating with subspace constraint
Author(s): Kai-Bor Yu
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Paper Abstract

An algorithm is presented for updating the adaptive beamformer weights using recursive eigenvalue decomposition (EVD) of a covariance matrix and subspace constraint. This algorithm exploits the subspace structure that the covariance matrix of the interference sources and the noise is a low-rank matrix plus a diagonal matrix. This eigenspace characterization approach avoids the numerically unstable recursive procedure based on the matrix inversion lemma. Moreover, the subspace property makes it possible to develop a fast algorithm by monitoring only the principal eigenvalues and eigenvectors and the noise eigenvalue.

Paper Details

Date Published: 1 December 1991
PDF: 8 pages
Proc. SPIE 1565, Adaptive Signal Processing, (1 December 1991); doi: 10.1117/12.49763
Show Author Affiliations
Kai-Bor Yu, GE Corporate Research and Development (United States)


Published in SPIE Proceedings Vol. 1565:
Adaptive Signal Processing
Simon Haykin, Editor(s)

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