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Interference-plus-Noise Covariance Matrix Reconstruction via Spatial Power Spectrum Sampling for Robust Adaptive Beamforming

Zhang, Zhenyu ; Liu, Wei ; Leng, Wen ; Wang, Anguo ; Shi, Heping

IEEE signal processing letters, 2016-01, Vol.23 (1), p.121-125 [Periódico revisado por pares]

New York: IEEE

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Título:
Interference-plus-Noise Covariance Matrix Reconstruction via Spatial Power Spectrum Sampling for Robust Adaptive Beamforming
Autor: Zhang, Zhenyu ; Liu, Wei ; Leng, Wen ; Wang, Anguo ; Shi, Heping
Assuntos: Algorithms ; Approximation methods ; Array signal processing ; Arrays ; Beamforming ; Computer simulation ; Covariance ; Covariance matrices ; Covariance matrix ; Covariance matrix reconstruction ; Estimators ; Image reconstruction ; matrix taper ; Reconstruction ; robust beamforming ; Robustness ; Sampling ; spatial power spectrum sampling ; Spectral analysis
É parte de: IEEE signal processing letters, 2016-01, Vol.23 (1), p.121-125
Notas: ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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Descrição: Recently, a robust adaptive beamforming (RAB) technique based on interference-plus-noise covariance (INC) matrix reconstruction has been proposed, which utilizes the Capon spectrum estimator integrated over a region separated from the direction of the desired signal. Inspired by the sampling and reconstruction idea, in this paper, a novel method named spatial power spectrum sampling (SPSS) is proposed to reconstruct the INC matrix more efficiently, with the corresponding beamforming algorithm developed, where the covariance matrix taper (CMT) technique is employed to further improve its performance. Simulation results are provided to demonstrate the effectiveness of the proposed method.
Editor: New York: IEEE
Idioma: Inglês

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Interference-plus-Noise Covariance Matrix Reconstruction via Spatial Power Spectrum Sampling for Robust Adaptive Beamforming

Zhang, Zhenyu ; Liu, Wei ; Leng, Wen ; Wang, Anguo ; Shi, Heping

New York: IEEE

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