An algorithm for linearly constrained adaptive array processing

By O. Frost. 1972

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Citations in the corpus

Voice Separation with an Unknown Number of Multiple Speakers (2020, background): “, 2009), the authors present an extension to the minimum variance distortionless response (MVDR) beamformer (Capon, 1969; Frost, 1972).”
AudioGen: Textually Guided Audio Generation (2022, background): “Audio is intrinsically a one dimensional signal and thus has less degrees of freedom to differentiate overlapping “objects” (Capon, 1969; Frost, 1972).”
Multichannel Eigenspace Beamforming in a Reverberant Noisy Environment With Multiple Interfering Speech Signals (2009, background): “In an MVDR beamformer [15], [16], the power of the output signal is minimized under the constraint that signals arriving from the assumed direction of the desired speech source are processed without distortion.”
Self-initiating MUSIC-based direction finding and polarization estimation in spatio-polarizational beamspace (2000, background): “3) Why Use Spatio-Polarizational Beamspace?:An electromagnetic vector sensor, with its six constituent antennas, may form spatio-polarizational beams (for example, via linearly constrained minimum variance (LCMV) beamforming [ 1 ]) to pass only a signal-of-interest along certain angular/polarization”
Signal enhancement using beamforming and nonstationarity with applications to speech (2001, methodology): “By following the derivation of [1] in the frequency domain, we derive a beamforming algorithm for the general TF case.”
A Consolidated Perspective on Multimicrophone Speech Enhancement and Source Separation (2017, unknown): “Given j (cid:63) ( n, f ) and θ , it turns out that the optimal value of the predominant source is obtained by the MVDR beamformer s (cid:63)j ( n, f ) = w H MVDR ( f ) x ( n, f ) where w MVDR ( f ) is given by (43) by identifying a 1 with a (cid:63)j ( f ) and setting q = 1 .”
Principles of minimum variance robust adaptive beamforming design (2013, methodology): “Depending on the choice of C or f, we may have point or derivative mainbeam constraints [3,88].”
Constrained band selection for hyperspectral imagery (2006, methodology): “One is to convert a band image to a band image vector and the data sample correlation matrix used in the CEM is then replaced with a correlation matrix obtained by averaging the individual band image correlation matrix.”
Geometric source separation: merging convolutive source separation with geometric beamforming (2001, methodology): “This concept is used in the linearly constrained minimum variance (LCMV) algorithm and is also the underlying idea for the generalized sidelobe canceler [15], [16].”
Robust Wideband Adaptive Beamforming With Null Broadening and Constant Beamwidth (2019, methodology): “Array beampatterns of Frost, FI constraints, and proposed methods are investigated, and the corresponding results are shown in Fig.”
Salient Band Selection for Hyperspectral Image Classification via Manifold Ranking (2016, background): “This idea can be traced back to the linearly constrained minimum variance (LCMV) [47] and the induced algorithms are similarly denoted as LCMV-BCM and LCMV-BCC.”
Microphone array processing for distant speech recognition: Towards real-world deployment (2012, unknown): “1] [26]”
On robust Capon beamforming and diagonal loading (2003, methodology): “In this paper, we focus on SOI power estimation problem, but the robust beamforming approach we present herein can also be used for other applications including signal waveform estimation [8], [9], [28].”