DocumentCode :
643713
Title :
Robust adaptive beamforming method based on interference-plus-noise covariance matrix
Author :
Yunshan Hou ; Lin Xue ; Yong Jin
Author_Institution :
Coll. of Electron. & Inf. Eng., Henan Univ. of Sci. & Technol., Luoyang, China
fYear :
2013
fDate :
5-8 Aug. 2013
Firstpage :
1
Lastpage :
4
Abstract :
In order to improve the performance of adaptive beamforming, this paper proposes a robust adaptive beamforming algorithm. In this algorithm, first the signal-free interference-plus-noise covariance matrix is reconstructed using MUSIC spatial spectrum as the power density distribution, then the optimization problem of estimating the desired signal steering vector is formulated by maximizing the array output power and adopting spherical set constraint, next the Lagrange multiplier method is employed to yield the computing formula of the optimal steering vector of desired signal. Simulation results demonstrate that the performance of proposed adaptive beamformer is almost always close to optimal in a very large range of signal-to-noise ratio(SNR), outperforming existing adaptive beamformers.
Keywords :
adaptive signal processing; array signal processing; covariance matrices; estimation theory; interference (signal); optimisation; signal classification; signal reconstruction; vectors; Lagrange multiplier method; MUSIC spatial spectrum; SNR; array output power maximization; multiple signal classification; optimal signal steering vector estimation; optimization problem; power density distribution; robust adaptive beamforming method; signal reconstruction; signal-free interference-plus-noise covariance matrix; signal-to-noise ratio; spherical set constraint; Array signal processing; Arrays; Covariance matrices; Interference; Robustness; Signal to noise ratio; Vectors; Adaptive beamforming; Signal to Interference plus Noise Ratio(SINR); Spatial spectrum; Steering vector;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing, Communication and Computing (ICSPCC), 2013 IEEE International Conference on
Conference_Location :
KunMing
Type :
conf
DOI :
10.1109/ICSPCC.2013.6664033
Filename :
6664033
Link To Document :
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