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New Convex Approaches to General MVDR Robust Adaptive Beamforming Problems
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  • Yao Zhao,
  • Qingsong Liu,
  • He Tian,
  • Mingfan Luo,
  • Bingo Ling,
  • Zhe Zhang
Yao Zhao
Guangdong University of Technology
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Qingsong Liu
Guangdong University of Technology
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He Tian
Science and Technology on Electromagnetic Scattering Laboratory
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Mingfan Luo
Surveying and Mapping Institute Lands and Resource Department of Guangdong Province
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Bingo Ling
Guangdong University of Technology
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Zhe Zhang
Aerospace Information Research Institute, Chinese Academy of Sciences

Corresponding Author:[email protected]

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Consider general minimum variance distortionless response (MVDR) robust adaptive beamforming problems based on the optimal estimation for both the desired signal steering vector and the interference-plus-noise covariance (INC) matrix. The optimal robust adaptive beamformer design problem is an array output power maximization problem, subject to three constraints on the steering vector, namely, a (convex or nonconvex) quadratic constraint ensuring that the direction-of-arrival (DOA) of the desired signal is separated from the DOA region of all linear combinations of the interference steering vectors, a double-sided norm constraint, and a similarity constraint; as well as a ball constraint on the INC matrix, which is centered at a given data sample covariance matrix. To tackle the nonconvex problem, a new tightened semidefinite relaxation (SDR) approach is proposed to output a globally optimal solution; otherwise, a sequential convex approximation (SCA) method is established to return a locally optimal solution. The simulation results show that the MVDR robust adaptive beamformers based on the optimal estimation for the steering vector and the INC matrix have better performance (in terms of, e.g., the array output signal-to-interference-plus-noise ratio) than the existing MVDR robust adaptive beamformers by the steering vector estimation only.
13 Aug 2023Submitted to Electronics Letters
14 Aug 2023Submission Checks Completed
14 Aug 2023Assigned to Editor
14 Aug 2023Reviewer(s) Assigned
16 Aug 2023Review(s) Completed, Editorial Evaluation Pending
17 Aug 2023Editorial Decision: Revise Major
06 Sep 20231st Revision Received
07 Sep 2023Submission Checks Completed
07 Sep 2023Assigned to Editor
07 Sep 2023Review(s) Completed, Editorial Evaluation Pending
07 Sep 2023Reviewer(s) Assigned
12 Sep 2023Editorial Decision: Accept