A Distributionally Robust Minimum Variance Beamformer Design

作者：Li, Bin^*; Rong, Yue; Sun, Jie; Teo, Kok Lay

来源：IEEE Signal Processing Letters, 2018, 25(1): 105-109.

DOI：10.1109/LSP.2017.2773601

• Distributionally robust optimization
• gaussian robust beamformer
• robust minimum variance beamformer (RMVB)
• worst-case robust beamformer

This letter is concerned with a robust minimum variance beamformer design. To hedge the mismatch between the true and the assumed steering vectors, a distributionally robust beamformer (DR-beamformer) is proposed. The tractable reformulation of this beamformer is developed. Compared with the existing robust beamformers (e.g., worst-case robust beamformer and Gaussian robust beamformer), the proposed robust beamformer does not assume full knowledge of the channel mismatch. Therefore, it is more flexible in practice and more general in formulation. In addition, the relationships of the proposed robust beamformer to the existing ones are investigated. The performance gain of the DR-beamformer over the other robust beamformers is highlighted through numerical simulations.

• 出版日期2018-1
• 单位四川大学