| Title | On the Efficient Implementation and Time-Updating of the Linearly Constrained Minimum Variance Beamformer |
| Authors | Andreas Jakobsson, Stephen Alty |
| Full-text | Available as PDF, Restricted Access |
| Alternative Location | http://ieeexplore.ieee.org/..., Restricted Access |
| Alternative Location | http://www.eurasip.org/Proc..., Restricted Access |
| Publication | IEEE transactions on circuits and systems. 2 : a publication of the IEEE Circuits and Systems Society |
| Year | 2006 |
| Volume | 53 |
| Issue | 10 |
| Pages | 1059 - 1062 |
| Document type | Conference paper |
| Conference name | 14th European Signal Processing Conference |
| Conference Date | 2006-09-04 |
| Conference Location | Florence |
| Status | Published |
| Quality controlled | Yes |
| Language | eng |
| Publisher | IEEE |
| Abstract English | The linearly constrained minimum variance (LCMV) method<br> is an extension of the classical minimum variance distortionless<br> response (MVDR) filter, allowing for multiple linear<br> constraints. Depending on the spatial filter length and<br> the desired frequency grid, a direct computation of the resulting<br> spatial beampattern may be prohibitive. In this paper,<br> we exploit the rich structure of the LCMV expression to find<br> a non-recursive computationally efficient implementation of<br> the LCMV beamformer with fixed constraints. We then extend<br> this implementation by means of its time-varying displacement<br> structure to derive an efficient time-updating algorithm<br> of the spatial spectral estimate. Numerical simulations<br> indicate a dramatic computational gain, especially for large<br> arrays and fine frequency grids. |
| Keywords | adaptive signal processing, fine frequency grids, dramatic computational gain, fast Fourier transform, matrix inversion lemma, multiple linear constraints, spatial filters, spatial beam pattern, minimum variance beamformer, array signal processing, |
| ISBN/ISSN/Other | ISSN: 10577130 |
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