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CLC number: TN911.7
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2016-10-19
Cited: 1
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Low complexity robust adaptive beamforming for general-rank signal model with positive semidefinite constraint
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Yu-Tang Zhu, Jun-yong Liu, Yong-Bo Zhao, Jun Liu, Peng-Lang Shui. Low complexity robust adaptive beamforming for general-rank signal model with positive semidefinite constraint[J]. Frontiers of Information Technology & Electronic Engineering, 2016, 17(11): 1245-1252.
@article{title="Low complexity robust adaptive beamforming for general-rank signal model with positive semidefinite constraint",
author="Yu-Tang Zhu, Jun-yong Liu, Yong-Bo Zhao, Jun Liu, Peng-Lang Shui",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="17",
number="11",
pages="1245-1252",
year="2016",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1601112"
}
%0 Journal Article
%T Low complexity robust adaptive beamforming for general-rank signal model with positive semidefinite constraint
%A Yu-Tang Zhu
%A Jun-yong Liu
%A Yong-Bo Zhao
%A Jun Liu
%A Peng-Lang Shui
%J Frontiers of Information Technology & Electronic Engineering
%V 17
%N 11
%P 1245-1252
%@ 2095-9184
%D 2016
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1601112
TY - JOUR
T1 - Low complexity robust adaptive beamforming for general-rank signal model with positive semidefinite constraint
A1 - Yu-Tang Zhu
A1 - Jun-yong Liu
A1 - Yong-Bo Zhao
A1 - Jun Liu
A1 - Peng-Lang Shui
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 17
IS - 11
SP - 1245
EP - 1252
%@ 2095-9184
Y1 - 2016
PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.1601112
Abstract: We propose a low complexity robust beamforming method for the general-rank signal model, to combat against mismatches of the desired signal array response and the received signal covariance matrix. The proposed beamformer not only considers the norm bounded uncertainties in the desired and received signal covariance matrices, but also includes an additional positive semidefinite constraint on the desired signal covariance matrix. Based on the worst-case performance optimization criterion, a computationally simple closed-form weight vector is obtained. Simulation results verify the validity and robustness of the proposed beamforming method.
[1]Capon, J., 1969. High-resolution frequency-wavenumber spectrum analysis. Proc. IEEE, 57(8):1408-1418.
[2]Chen, H., Gershman, A.B., 2008. Robust adaptive beamforming for general-rank signal models with positive semi-definite constraint. IEEE Int. Conf. on Acoustics, Speech and Signal Processing, p.2341-2344.
[3]Chen, H., Gershman, A.B., 2011. Worst-case based robust adaptive beamforming for general-rank signal models using positive semi-definite covariance constraint. IEEE Int. Conf. on Acoustics, Speech and Signal Processing, p.2628-2631.
[4]Cirrincione, G., Cirrincione, M., Hérault, J., et al., 2002. The MCA EXIN neuron for the minor component analysis. IEEE Trans. Neur. Netw., 13(1):160-187.
[5]Cox, H., Zeskind, R., Owen, M., 1987. Robust adaptive beamforming. IEEE Trans. Acoust. Speech Signal Process., 35(10):1365-1376.
[6]de Maio, A., de Nicola, S., Farina, A., et al., 2010. Adaptive detection of a signal with angle uncertainty. IET Radar Sonar Navig., 4(4):537-547.
[7]Grant, M., Boyd, S., Ye, Y.Y., 2015. CVX: MATLAB Software for Disciplined Convex Programming. Available from http://cvxr.com/cvx/.
[9]Hassanien, A., Vorobyov, S.A., Wong, K.M., 2008. Robust adaptive beamforming using sequential programming: an iterative solution to the mismatch problem. IEEE Signal Process. Lett., 15:733-736.
[10]Khabbazibasmenj, A., Vorobyov, S.A., 2013. Robust adaptive beamforming for general-rank signal model with positive semi-definite constraint via POTDC. IEEE Trans. Signal Process., 61(23):6103-6117.
[11]Li, J., Stoica, P., Wang, Z.S., 2003. On robust capon beamforming and diagonal loading. IEEE Trans. Signal Process., 51(7):1702-1715.
[12]Shahbazpanahi, S., Gershman, A.B., Luo, Z.Q., et al., 2003. Robust adaptive beamforming for general-rank signal models. IEEE Trans. Signal Process., 51(9):2257-2269.
[13]Trump, T., Ottersten, B., 1996. Estimation of nominal direction of arrival and angular spread using an array of sensors. Signal Process., 50(1-2):57-69.
[14]van Trees, H.L., 2002. Optimum Array Processing: Part IV of Detection, Estimation, and Modulation Theory. John Wiley & Sons, New York, USA.
[16]Vorobyov, S.A., Gershman, A.B., Luo, Z.Q., 2003. Robust adaptive beamforming using worst-case performance optimization: a solution to the signal mismatch problem. IEEE Trans. Signal Process., 51(2):313-324.
[17]Zhang, L., Liu, W., 2012a. Robust forward backward based beamformer for a general-rank signal model with real-valued implementation. Signal Process., 92(1):163-169.
[18]Zhang, L., Liu, W., 2012b. Robust beamforming for coherent signals based on the spatial-smoothing technique. Signal Process., 92(11):2747-2758.
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