IEEE Transactions on Acoustics Speech and Signal Processing · 1990 · 215 citations · 13 references
EngineeringElectrical EngineeringAcousticsMusic AnalysisWireless CommunicationsAcoustic LocalizationArray ProcessingBeamformingDigital Signal ProcessingThreshold EstimationBeamforming AlgorithmsBeamspace ProcessingMusic AlgorithmSignal-to-noise RatioSignal-to-noise Ratio EstimationSignal-to-noise Ratio OptimizationSubspace IdentificationSubspace Learning
An analysis of a beamspace version of the MUSIC algorithm applicable to two closely spaced emitters in diverse scenarios is presented. Specifically, the analysis is applicable to uncorrelated far-field emitters of any relative power level, confined to a known plane, and observed by an arbitrary array of omnidirectional sensors. An expression for the threshold array signal-to-noise ratio at which beamspace MUSIC is able to resolve the emitters is obtained. The preprocessor that minimizes the resolution threshold is identified. It is demonstrated that the resolution threshold is proportional to the dimension of the noise subspace; therefore, the threshold can be reduced substantially by utilizing an appropriate beamformer to reduce the dimension of the noise subspace. It is also demonstrated that MUSIC in conjunction with a suitable preprocessor can provide a resolution threshold lower than conventional (sensor-space) MinNorm.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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The algebraic eigenvalue problem
V.V. Voyevodin · USSR Computational Mathematics and Mathematical Physics · 1966 · 2.1K citations