DocumentCode
1112485
Title
A multiple time scale modularized adaptive beamformer
Author
Niezgoda, G.H. ; Krolik, J.L.
Author_Institution
Dept. of Electr. & Comput. Eng., R. Mil. Coll. of Canada, Kingston, Ont., Canada
Volume
42
Issue
5
fYear
1994
fDate
5/1/1994 12:00:00 AM
Firstpage
1251
Lastpage
1256
Abstract
This paper analyzes the cascaded equivalent form of the minimum variance distortionless response (MVDR) beamformer. A unique feature of the modularized MVDR (M2VDR) beamformer is the ability to distribute adaptive degrees of freedom (DOF) among beamformer stages. This property of the M2VDR beamformer allows DOF to be adapted over different time scales. As a consequence of the multiple stage decomposition adaptive beamformer weights appear in a form which suggest an apparent increase in the number of DOF. To properly analyze this ease an alternative interpretation of adaptive DOF is introduced to establish the equivalence between the MVDR beamformer and its cascaded realization. In the second part of this paper the distribution for the output power estimate of a P stage M2VDR beamformer is derived. Analysis reveals the necessity of placing constraints on the adaptation time assigned to each beamformer stage. Simulation experiments are presented that demonstrate the applicability of the M 2VDR beamformer in resolving closely spaced sources under impulsive interference conditions
Keywords
acoustic signal processing; acoustic wave interference; array signal processing; signal detection; acoustic sources; adaptation time; adaptive beamformer weights; adaptive degrees of freedom; closely spaced sources; impulsive interference; minimum variance distortionless response; modularized adaptive beamformer; multiple stage decomposition; multiple time scale beamformer; output power estimate distribution; simulation experiments; Acoustic distortion; Adaptive signal processing; Algorithm design and analysis; Backpropagation algorithms; Classification algorithms; Least squares approximation; Neural networks; Signal processing algorithms; Speech processing; System identification;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/78.295189
Filename
295189
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