Abstract
Broadband adaptive beamforming algorithms based on the least mean square (LMS) family are known to exhibit slow convergence, if the input is correlated. In this paper, we will utilised a recently proposed broadband eigen value decomposition method to provide strong spatial decorrelation, while at the same time reduces the subspace in which the beamforming algorithm operates. Additional temporal decorrelation is gained by operating the beamformer in oversampled filter banks. Hybrid structures which combine both spatial and temporal decorrelation demonstrate to provide faster convergence speed than the normalised LMS algorithm or either of the decorrelation approach on its own.
Original language | English |
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Pages | 889-893 |
Number of pages | 4 |
Publication status | Published - Aug 2009 |
Event | 17th European Signal Processing Conference - Glasgow, Scotland Duration: 24 Aug 2009 → 28 Aug 2009 |
Conference
Conference | 17th European Signal Processing Conference |
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City | Glasgow, Scotland |
Period | 24/08/09 → 28/08/09 |
Keywords
- Broadband adaptive beamforming algorithms
- least mean square
- convergence
- broadband eigen value decomposition method