A Bayesian approach to robust adaptive beamforming

An adaptive beamformer that is robust to uncertainty in source direction-of-arrival (DOA) is derived using a Bayesian approach. The DOA is assumed to be a discrete random variable with a known a priori probability density function (PDF) that reflects the level of uncertainty in the source DOA. The r...

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Bibliographic Details
Published in:IEEE transactions on signal processing 2000-02, Vol.48 (2), p.386-398
Main Authors: Bell, K.L., Ephraim, Y., Van Trees, H.L.
Format: Article
Language:English
Subjects:
Applied sciences
Approximation
Array signal processing
Bayesian analysis
Bayesian methods
Degradation
Direction of arrival estimation
Distortion
Exact sciences and technology
Information, signal and communications theory
Interference suppression
Mathematical analysis
Miscellaneous
Probability density function
Probability density functions
Radiocommunications
Random variables
Robustness
Sensor arrays
Signal processing
Telecommunications
Telecommunications and information theory
Uncertainty
Variance
Vectors (mathematics)
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Summary:An adaptive beamformer that is robust to uncertainty in source direction-of-arrival (DOA) is derived using a Bayesian approach. The DOA is assumed to be a discrete random variable with a known a priori probability density function (PDF) that reflects the level of uncertainty in the source DOA. The resulting beamformer is a weighted sum of minimum variance distortionless response (MVDR) beamformers pointed at a set of candidate DOAs, where the relative contribution of each MVDR beamformer is determined from the a posteriori PDF of the DOA conditioned on previously observed data. A simple approximation to the a posteriori PDF results in a straightforward implementation. Performance of the approximate Bayesian beamformer is compared with linearly constrained minimum variance (LCMV) beamformers and data-driven approaches that attempt to estimate signal characteristics or the steering vector from the data.
ISSN:1053-587X
1941-0476
DOI:10.1109/78.823966