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22 October 1996 One-sided algorithm for subspace projection beam-forming
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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.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mark A.G. Smith and Ian K. Proudler "One-sided algorithm for subspace projection beam-forming", Proc. SPIE 2846, Advanced Signal Processing Algorithms, Architectures, and Implementations VI, (22 October 1996);

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