2002
DOI: 10.1006/dspr.2002.0450
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Short Data Record Adaptive Filtering: The Auxiliary-Vector Algorithm

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Cited by 3 publications
(2 citation statements)
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“…Maximizing (2) is equivalent to minimizing 1/SINR, as follows: (4) Observing that the cost function above is unaltered when is scaled, we can impose, without a loss of generality, the constraint , which can always be achieved by scaling . Hence, the maximization of the output SINR is equivalent to subject to (5) The solution to (5) is the well-known MVDR beamformer, given by solving (6) where serves to satisfy the unity gain constraint in (5).…”
Section: Mvdr Beamformingmentioning
confidence: 99%
See 1 more Smart Citation
“…Maximizing (2) is equivalent to minimizing 1/SINR, as follows: (4) Observing that the cost function above is unaltered when is scaled, we can impose, without a loss of generality, the constraint , which can always be achieved by scaling . Hence, the maximization of the output SINR is equivalent to subject to (5) The solution to (5) is the well-known MVDR beamformer, given by solving (6) where serves to satisfy the unity gain constraint in (5).…”
Section: Mvdr Beamformingmentioning
confidence: 99%
“…To maximize performance in a nonstationary scenario, adaptive beamforming (ABF) is necessary. In rapidly changing scenarios, only a limited number of snapshots is available to estimate the covariance matrix; under these circumstances, the low-rank minimum variance distortionless response (MVDR) equations yield faster convergence in terms of the signal-to-interference-plus-noise ratio (SINR) performance than the full-rank MVDR beamformer [2]- [5]. Owsley [6] introduced dominant mode rejection (DMR) low-rank ABF.…”
Section: Introductionmentioning
confidence: 99%