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PIER PIER B PIER C PIER M PIER Letters PIER Photonics
2014-06-16
Magnitude Constraint Minimum Variance Beamformer with Conjugate Symmetric Constraint and Norm Constraint
By
Lulu Zhao,

    Dr. Lulu Zhao

    Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Science

    China

    Homepage

Guang Liang,

    Professor Guang Liang

    Chinese Academy of Science

    China

    Homepage

Huijie Liu

    Dr. Huijie Liu

    Chinese Academy of Science

    China

    Homepage

Progress In Electromagnetics Research M, Vol. 37, 41-50, 2014
doi:10.2528/PIERM14042808 | Google Scholar

Abstract
In this paper, an improved robust minimum variance beamformer against direction of arrival (DOA) mismatch and finite sample effect is proposed. Multiple inequality magnitude constraints are imposed to broaden the main lobe of beampattern. The conjugate symmetric structure of the optimal weight is utilized to transform the non-convex inequality magnitude constraints into convex ones. A quadratic constraint on the norm of weight is introducing to make further improvement on robustness against DOA mismatch and finite sample effect. The proposed beamforming problem can be reformulated in the form of the second order cone programming and solved efficiently by interior point method. Simulation results show that the proposed beamformer outperforms several other adaptive beamformers.
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Citation
Lulu Zhao, Guang Liang, and Huijie Liu, "Magnitude Constraint Minimum Variance Beamformer with Conjugate Symmetric Constraint and Norm Constraint," Progress In Electromagnetics Research M, Vol. 37, 41-50, 2014.
doi:10.2528/PIERM14042808
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