Full Text:   <650>

Summary:  <338>

CLC number: TN911.7

On-line Access: 2016-11-07

Received: 2016-03-27

Revision Accepted: 2016-09-14

Crosschecked: 2016-10-19

Cited: 1

Clicked: 1762

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Yu-Tang Zhu

http://orcid.org/0000-0002-6826-4307

-   Go to

Article info.
Open peer comments

Frontiers of Information Technology & Electronic Engineering  2016 Vol.17 No.11 P.1245-1252

http://doi.org/10.1631/FITEE.1601112


Low complexity robust adaptive beamforming for general-rank signal model with positive semidefinite constraint


Author(s):  Yu-Tang Zhu, Jun-yong Liu, Yong-Bo Zhao, Jun Liu, Peng-Lang Shui

Affiliation(s):  National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China

Corresponding email(s):   yutangzhu_xd@163.com

Key Words:  Beamforming, General-rank, Low complexity, Positive semidefinite (PSD) constraint, Model mismatches


Share this article to: More <<< Previous Article|

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
ER -
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.

基于正定约束广义秩信号模型的低复杂度稳健自适应算法

概要:本文针对广义秩信号模型提出一种低复杂度的稳健自适应波束形成算法,用来抑制期望信号的阵列响应失配和接收信号的协方差矩阵失配。该波束形成算法不仅考虑期望信号以及接收信号协方差矩阵不确定集的范数有界性,还保证期望信号协方差矩阵的正定性。最终,本文在最差性能优化准则下推出一个计算简单的闭式加权矢量。计算机仿真结果验证了所提波束形成算法的有效性和稳健性。

关键词:波束形成;广义秩;低复杂度;正定约束;模型失配

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[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/. 8 IEEE Trans. Signal Process., 60(7):3881-3885.

[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. 15 Signal Process., 93(12): 3264-3277.

[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.

Open peer comments: Debate/Discuss/Question/Opinion

<1>

Please provide your name, email address and a comment





Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - Journal of Zhejiang University-SCIENCE