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On the Efficient Implementation and Time-Updating of the Linearly Constrained Minimum Variance Beamformer

Jakobsson, Andreas LU and Alty, Stephen (2006) 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:
author
publishing date
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.
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
2019-03-08 02:33:39
@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},
  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          = {https://lup.lub.lu.se/search/ws/files/4394356/1274667.pdf},
  volume       = {53},
  year         = {2006},
}