Fast stable parallel adaptive beamforming using conjugate directions

A new fast-converging numerically stable parallel algorithm of adaptive antenna beamforming is introduced. The algorithm builds the conjugate-direction decomposition (CDD) of the optimal transversal filter weight vector using a novel stabilized parallel version of the Gram-Schmidt orthogonalization...

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Bibliographic Details
Published in2005 IEEE Antennas and Propagation Society International Symposium Vol. 3A; pp. 283 - 286 vol. 3A
Main Author Khlebnikov, V.A.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2005
Subjects
Adaptive arrays
Array signal processing
Convergence of numerical methods
Covariance matrix
Decorrelation
Filters
Linear antenna arrays
Matrix decomposition
Parallel processing
Radar antennas
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Summary:A new fast-converging numerically stable parallel algorithm of adaptive antenna beamforming is introduced. The algorithm builds the conjugate-direction decomposition (CDD) of the optimal transversal filter weight vector using a novel stabilized parallel version of the Gram-Schmidt orthogonalization (GSO). The numerical robustness of the modified GSO version is achieved through a bootstrapped mechanism of parallel crossed feedbacks. Regarding the number of independent input samples, the new algorithm has the same convergence as that of the widely used sample matrix inversion (SMI) method, but its real time of adaptation appears to be much faster due to the high degree of parallelism, reduced numerical complexity, and ability to be implemented with fix-point arithmetic.
ISBN:9780780388833
0780388836
ISSN:1522-3965
1947-1491
DOI:10.1109/APS.2005.1552236