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22 October 1996One-sided algorithm for subspace projection beam-forming
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.
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Mark A.G. Smith, 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); https://doi.org/10.1117/12.255424