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Robust Beamforming Based on Weighted Vector Norm Regularization
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DOI：10.1109/ACCESS.2021.3090104.png)
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Abstract
En 中文
Steering vector mismatch rapidly degrades the performance of the minimum variance distortionless response beamformer. To solve this problem, a robust beamforming method based on weighted vector norm regularization is proposed. First, the factors affecting the robustness of the beamformer are analyzed. Second, by introducing the weighted vector norm, an optimization problem is constructed to increase the robustness of the beamformer. Furthermore, the regularization coefficient is provided to achieve a balance between the output power and the robustness of the beamformer. Meanwhile, a method of finding the appropriate regularization coefficient is provided. Then, simulations of an irregular arc array are carried out, showing that the proposed method is robust to the snapshot number. Finally, the results and data analysis indicate the effectiveness of the proposed method.
Keywords:
Array signal processing
Interference
Robustness
Signal to noise ratio
Loading
Covariance matrices
Power generation
Beamforming
robustness
regularization
spatial resolution
weighted vector norm
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