The PDF of adaptive beamforming weights

The author derives a closed-form expression for the marginal probability density function (PDF) for the weight vector coefficients in a minimum-variance distortionless response (MVDR) adaptive beamformer, when the snapshots are independently identically distributed (IID) normal and the weights are c...

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Bibliographic Details
Published in:IEEE transactions on signal processing 1991-05, Vol.39 (5), p.1232-1235
Main Author: Steinhardt, A.O.
Format: Article
Language:English
Subjects:
Array signal processing
Automatic control
Covariance matrix
Degradation
Density functional theory
Dynamic range
Interference
Least squares approximation
Maximum likelihood estimation
Societies
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Summary:The author derives a closed-form expression for the marginal probability density function (PDF) for the weight vector coefficients in a minimum-variance distortionless response (MVDR) adaptive beamformer, when the snapshots are independently identically distributed (IID) normal and the weights are computed via sample matrix inversion. The marginal PDF allows one to determine the dynamic range required to avoid saturation (with a specified degree of probability) in digital and/or analog implementation of beamforming weights.< >
ISSN:1053-587X
1941-0476
DOI:10.1109/78.80979