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

Yu-tang ZHU; Yong-bo ZHAO; Jun LIU; Peng-lang SHUI

doi:10.1631/FITEE.1601112

Your Location：

Home >

Browse articles >

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

Regular Papers | Updated：2022-05-19

- Low complexity robust adaptive beamforming for general-rank signal model with positive semidefinite constraint
  Enhanced Publication
- 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
- Frontiers of Information Technology & Electronic Engineering Vol. 17, Issue 11, Pages: 1245-1252(2016)
- Affiliations：
  
  National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China
- Author bio：
  
  E-mail:yutangzhu_xd@163.com
- Funds：
- DOI：10.1631/FITEE.1601112
  CLC： TN911.7
- Published：2016-11，
  
  Received：27 February 2016，
  
  Accepted：2016-9-14
- Accepted：
Scan QR Code
YU-TANG ZHU, YONG-BO ZHAO, JUN LIU, et al. 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.
DOI：

YU-TANG ZHU, YONG-BO ZHAO, JUN LIU, et al. 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. DOI： 10.1631/FITEE.1601112.

摘要

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。

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.

关键词

波束形成广义秩低复杂度正定约束模型失配

Keywords

BeamformingGeneral-rankLow complexityPositive semidefinite (PSD) constraintModel mismatches

references

J Capon..High-resolution frequency-wavenumber spectrum analysis..Proc. IEEE,,1969..57((8):):1408--1418..DOI:10.1109/PROC.1969.7278http://doi.org/10.1109/PROC.1969.7278..

H Chen,,,AB Gershman..Robust adaptive beamforming for general-rank signal models with positive semi-definite constraint..2008..IEEE Int. Conf. on Acoustics, Speech and Signal Processing..2341--2344..DOI:10.1109/ICASSP.2008.4518116http://doi.org/10.1109/ICASSP.2008.4518116..

H Chen,,,AB Gershman..Worst-case based robust adaptive beamforming for general-rank signal models using positive semi-definite covariance constraint..2011..IEEE Int. Conf. on Acoustics, Speech and Signal Processing..2628--2631..DOI:10.1109/ICASSP.2011.5947024http://doi.org/10.1109/ICASSP.2011.5947024..

G Cirrincione,,,M Cirrincione,,,J H rault,,,等..The MCA EXIN neuron for the minor component analysis..IEEE Trans. Neur. Netw.,,2002..13((1):):160--187..DOI:10.1109/72.977295http://doi.org/10.1109/72.977295..

H Cox,,,R Zeskind,,,M Owen..Robust adaptive beamforming..IEEE Trans. Acoust. Speech Signal Process.,,1987..35((10):):1365--1376..DOI:10.1109/TASSP.1987.1165054http://doi.org/10.1109/TASSP.1987.1165054..

A de Maio,,,S de Nicola,,,A Farina,,,等..Adaptive detection of a signal with angle uncertainty..IET Radar Sonar Navig.,,2010..4((4):):537--547..DOI:10.1049/iet-rsn.2009.0106http://doi.org/10.1049/iet-rsn.2009.0106..

M Grant,,,S Boyd,,,YY Ye..CVX: MATLAB Software for Disciplined Convex Programming,,2015..Available fromhttp://cvxr.com/cvx/http://cvxr.com/cvx/..

Y Gu,,,A Leshem..Robust adaptive beamforming based on interference covariance matrix reconstruction and steering vector estimation..IEEE Trans. Signal Process.,,2012..60((7):):3881--3885..DOI:10.1109/TSP.2012.2194289http://doi.org/10.1109/TSP.2012.2194289..

A Hassanien,,,SA Vorobyov,,,KM Wong..Robust adaptive beamforming using sequential programming: an iterative solution to the mismatch problem..IEEE Signal Process. Lett.,,2008..15733--736..DOI:10.1109/LSP.2008.2001115http://doi.org/10.1109/LSP.2008.2001115..

A Khabbazibasmenj,,,SA Vorobyov..Robust adaptive beamforming for general-rank signal model with positive semi-definite constraint via POTDC..IEEE Trans. Signal Process.,,2013..61((23):):6103--6117..DOI:10.1109/TSP.2013.2281301http://doi.org/10.1109/TSP.2013.2281301..

J Li,,,P Stoica,,,ZS Wang..On robust capon beam-forming and diagonal loading..IEEE Trans. Signal Process.,,2003..51((7):):1702--1715..DOI:10.1109/TSP.2003.812831http://doi.org/10.1109/TSP.2003.812831..

S Shahbazpanahi,,,AB Gershman,,,ZQ Luo,,,等..Robust adaptive beamforming for general-rank signal models..IEEE Trans. Signal Process.,,2003..51((9):):2257--2269..DOI:10.1109/TSP.2003.815395http://doi.org/10.1109/TSP.2003.815395..

T Trump,,,B Ottersten..Estimation of nominal direction of arrival and angular spread using an array of sensors..Signal Process.,,1996..50((1-2):):57--69..DOI:10.1016/0165-1684(96)00003-5http://doi.org/10.1016/0165-1684(96)00003-5..

HL van Trees..Optimum Array Processing: Part Ⅳ of Detection, Estimation, and Modulation Theory,,2002..:John Wiley & Sons, New York, USA:..

SA Vorobyov..Principles of minimum variance robust adaptive beamforming design..Signal Process.,,2012..93((12):):3264--3277..DOI:10.1016/j.sigpro.2012.10.021http://doi.org/10.1016/j.sigpro.2012.10.021..

SA Vorobyov,,,AB Gershman,,,ZQ Luo..Robust adaptive beamforming using worst-case performance op-timization: a solution to the signal mismatch problem..IEEE Trans. Signal Process.,,2003..51((2):):313--324..DOI:10.1109/TSP.2002.806865http://doi.org/10.1109/TSP.2002.806865..

L Zhang,,,W Liu..Robust forward backward based beamformer for a general-rank signal model with real-valued implementation..Signal Process.,,2012a..92((1):):163--169..DOI:10.1016/j.sigpro.2011.07.001http://doi.org/10.1016/j.sigpro.2011.07.001..

L Zhang,,,W Liu..Robust beamforming for coherent signals based on the spatial-smoothing technique..Signal Process.,,2012b..92((11):):2747--2758..DOI:10.1016/j.sigpro.2012.05.008http://doi.org/10.1016/j.sigpro.2012.05.008..

Views

Downloads

CSCD

Alert me when the article has been cited

Submit

Tools

Publicity Resources

Supermodular interference suppression game for multistatic MIMO radar networks and multiple jammers with multiple targets

Related Author

Bin HE

Hongtao SU

Related Institution

National Laboratory of Radar Signal Processing, Xidian University

The 54th Research Institute of CETC

Address：Zhejiang University Press, 148 Tianmushan Road, Hangzhou, China Postal code：310028
Tel：+86-571-88273162 Email：fitee@zju.edu.cn
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰