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Proceedings Paper

One-sided algorithm for subspace projection beam-forming
Author(s): Mark A.G. Smith; Ian K. Proudler
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Paper Abstract

Conventional least squares minimization beamforming algorithms suffer from `weight jitter' when small data sequences are used. One method for overcoming this problem requires that the SVD of the data matrix is calculated and the `signal' and `noise' subspaces identified. A more stable beampattern can then be formed by projecting the least squares weight vector onto the appropriate subspace. The SVD is computationally expensive to perform and difficult to implement in a parallel architecture. Several approximate `rank revealing' algorithms have been presented of late (e.g. URV, RRQR) which have a much reduced computational load. However, being `two-sided' decompositions, they all suffer from implementation difficulties. In this paper we present an algorithm, based on QR decomposition, that can approximately reveal the rank and signal subspace of a matrix and simultaneously perform a subspace projection. The algorithm has the potential for very simple parallel implementation.

Paper Details

Date Published: 22 October 1996
PDF: 12 pages
Proc. SPIE 2846, Advanced Signal Processing Algorithms, Architectures, and Implementations VI, (22 October 1996); doi: 10.1117/12.255424
Show Author Affiliations
Mark A.G. Smith, Defence Research Agency Malvern (United Kingdom)
Ian K. Proudler, Defence Research Agency Malvern (United Kingdom)


Published in SPIE Proceedings Vol. 2846:
Advanced Signal Processing Algorithms, Architectures, and Implementations VI
Franklin T. Luk, Editor(s)

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