Robust adaptive beamforming algorithm by constraints on magnitude response

被引：0

作者：

Wu, Renbin ^{[1
,2
]}

Yao, Minli ^{[3
]}

Jia, Weimin ^{[1
]}

Jin, Wei ^{[1
]}

Zou, Xiang ^{[4
]}

机构：

[1] Staff Room 907, The Second Artillery Engineering University

[2] Unit 96111 of PLA, Hancheng

[3] Staff Room 403, The Second Artillery Engineering University

[4] Post-Doctoral Research Center, Electronic Engineering Institute

来源：

Hsi-An Chiao Tung Ta Hsueh/Journal of Xi'an Jiaotong University | 2014年 / 48卷 / 04期

关键词：

Beamforming; Constraints on magnitude response; Multiple coherent signals; Robustness;

D O I：

10.7652/xjtuxb201404019

中图分类号：

学科分类号：

摘要：

Aiming at degradation of robustness caused by large steering vector mismatch in the traditional adaptive beamforming algorithms, a robust adaptive beamforming algorithm by constraints on magnitude response is proposed. The receiving covariance matrix mismatch is modeling optimized, and the main lobe magnitudes are then constrained according to the known direction information of multiple coherent signals. The optimization case is converted into an iterative second-order cone programming (SOCP) via the presented lemma. Simulations show that this method enables to form beam main lobe in the direction of multiple coherent signals, and to control the width and the ripple level of the main lobe flexibly. When direction mismatch of the desired signal reaches 3.5° and the signal to noise ratio (SNR) varies within -5 dB to 10 dB, the array output signal to interference and noise ratio (SINR) in the proposed algorithm is superior to that in the uncertainty algorithm by 0-6 dB, and this algorithm is endowed with higher robustness against large steering vector mismatch.

引用

页码：109 / 114

页数：5

共 12 条

[1]

Widrow B., Duvall K., Gooch R., Et al., Signal cancellation phenomena in adaptive antennas: causes and cures, IEEE Transactions on Antennas and Propagation, 30, 3, pp. 469-478, (1982)

[2]

Huang Z., Liu C., Tang X., Adaptive beam-forming of coherent signals based on second-order cone programming, Electronic Information Warfare Technology, 28, 2, pp. 10-14, (2013)

[3]

Lee T.S., Lin T.T., Coherent interference suppression with complementally transformed adaptive beamformer, IEEE Transactions on Antennas and Propagation, 46, 5, pp. 609-617, (1998)

[4]

Bresler Y., Reddy V.U., Kailath T., Optimum beamforming for coherent signal and interferences, IEEE Transactions on Acoustics, Speech and Signal Processing, 36, 6, pp. 833-843, (1988)

[5]

Dogan M.C., Mendel J.M., Cumulant-based blind optimum beamforming, IEEE Transactions on Aerospace and Electronic Systems, 30, 3, pp. 722-741, (1994)

[6]

Yu L., Liu W., Richard J.L., Robust beamforming methods for multipath signal reception, Digital Signal Processing, 20, 2, pp. 379-390, (2010)

[7]

Vorobyov S.A., Gershman A.B., Luo Z., Robust adaptive beamforming using worst-case performance optimization: a solution to the signal mismatch problem, IEEE Transactions on Signal Processing, 51, 2, pp. 313-324, (2003)

[8]

Yu Z., Ser W., Er M.H., Et al., Robust adaptive beamformers based on worst-case optimization and constraints on magnitude response, IEEE Transactions on Signal Processing, 57, 7, pp. 2615-2628, (2009)

[9]

Liao B., Tsui K.M., Chan S.C., Robust beamforming with magnitude response constraints using iterative second-order cone programming, IEEE Transactions on Antennas and Propagation, 59, 9, pp. 3477-3482, (2011)

[10]

Wang F., Balakrishnan V., Zhou P.Y., Et al., Optimal array pattern synthesis using semidefinite programming, IEEE Transactions on Signal Processing, 51, 5, pp. 1172-1183, (2003)

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