Adaptive beamforming using recursive eigenstructure updating with subspace constraint

Kai-Bor Yu

doi:10.1117/12.49763

1 December 1991 Adaptive beamforming using recursive eigenstructure updating with subspace constraint

Kai-Bor Yu

Proceedings Volume 1565, Adaptive Signal Processing; (1991) https://doi.org/10.1117/12.49763
Event: San Diego, '91, 1991, San Diego, CA, United States

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.

Citation Download Citation

Kai-Bor Yu "Adaptive beamforming using recursive eigenstructure updating with subspace constraint", Proc. SPIE 1565, Adaptive Signal Processing, (1 December 1991); https://doi.org/10.1117/12.49763

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