On the Efficient Implementation and Time-Updating of the Linearly Constrained Minimum Variance Beamformer
Jakobsson, Andreas LU
and Alty, Stephen
(2006)
14th European Signal Processing Conference
53(10).
p.1059-1062
- Abstract
- The linearly constrained minimum variance (LCMV) method
is an extension of the classical minimum variance distortionless
response (MVDR) filter, allowing for multiple linear
constraints. Depending on the spatial filter length and
the desired frequency grid, a direct computation of the resulting
spatial beampattern may be prohibitive. In this paper,
we exploit the rich structure of the LCMV expression to find
a non-recursive computationally efficient implementation of
the LCMV beamformer with fixed constraints. We then extend
this implementation by means of its time-varying displacement
structure to derive an efficient time-updating algorithm
... (More) - The linearly constrained minimum variance (LCMV) method
is an extension of the classical minimum variance distortionless
response (MVDR) filter, allowing for multiple linear
constraints. Depending on the spatial filter length and
the desired frequency grid, a direct computation of the resulting
spatial beampattern may be prohibitive. In this paper,
we exploit the rich structure of the LCMV expression to find
a non-recursive computationally efficient implementation of
the LCMV beamformer with fixed constraints. We then extend
this implementation by means of its time-varying displacement
structure to derive an efficient time-updating algorithm
of the spatial spectral estimate. Numerical simulations
indicate a dramatic computational gain, especially for large
arrays and fine frequency grids. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1274666
- author
- Jakobsson, Andreas
LU
and Alty, Stephen
- publishing date
- 2006
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- 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
- host publication
- IEEE transactions on circuits and systems. 2 : a publication of the IEEE Circuits and Systems Society
- volume
- 53
- issue
- 10
- pages
- 1059 - 1062
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 14th European Signal Processing Conference
- conference dates
- 2006-09-04
- external identifiers
-
- scopus:84862615867
- ISSN
- 1057-7130
- language
- English
- LU publication?
- no
- id
- d52069de-cb92-40a3-ae48-9a2149173f22 (old id 1274666)
- alternative location
- http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1715577
- http://www.eurasip.org/Proceedings/Eusipco/Eusipco2006/papers/1568981705.pdf
- date added to LUP
- 2016-04-01 15:26:45
- date last changed
- 2022-01-28 05:21:41
@inproceedings{d52069de-cb92-40a3-ae48-9a2149173f22,
abstract = {{The linearly constrained minimum variance (LCMV) method<br/><br>
is an extension of the classical minimum variance distortionless<br/><br>
response (MVDR) filter, allowing for multiple linear<br/><br>
constraints. Depending on the spatial filter length and<br/><br>
the desired frequency grid, a direct computation of the resulting<br/><br>
spatial beampattern may be prohibitive. In this paper,<br/><br>
we exploit the rich structure of the LCMV expression to find<br/><br>
a non-recursive computationally efficient implementation of<br/><br>
the LCMV beamformer with fixed constraints. We then extend<br/><br>
this implementation by means of its time-varying displacement<br/><br>
structure to derive an efficient time-updating algorithm<br/><br>
of the spatial spectral estimate. Numerical simulations<br/><br>
indicate a dramatic computational gain, especially for large<br/><br>
arrays and fine frequency grids.}},
author = {{Jakobsson, Andreas and Alty, Stephen}},
booktitle = {{IEEE transactions on circuits and systems. 2 : a publication of the IEEE Circuits and Systems Society}},
issn = {{1057-7130}},
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}},
language = {{eng}},
number = {{10}},
pages = {{1059--1062}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
title = {{On the Efficient Implementation and Time-Updating of the Linearly Constrained Minimum Variance Beamformer}},
url = {{http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1715577}},
volume = {{53}},
year = {{2006}},
}