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Abstract
Widely linear beamforming is known to outperform the conventional adaptive beamforming by fully employing the non-circularity of non-circular signals. In this paper, a robust widely linear beamformer (WLB) is proposed to achieve satisfactory output and robustness in low computational complexity. The augmented signal-of-interest (SOI) covariance matrix is built by performing integration over SOI angular sector. The principal eigenvector of the augmented SOI covariance matrix is taken as the SOI extended steering vector. The received signal vector is projected into the interference-plus-noise subspace to remove the SOI component and derive the augmented interference covariance matrix. The augmented noise covariance matrix is added to the derived augmented interference covariance matrix so that the augmented interference-plus-noise covariance matrix can be reconstructed. The proposed WLB possesses lower computational complexity than the state-of-the-art WLBs due to the avoidance of convex optimization programming. Numerical simulations illustrate the effectiveness of the proposed WLB.
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Notes on contributors
Zhen Meng
Zhen Meng received the B.S. degree and the Ph.D. degree from the Harbin Engineering University, Harbin, China, in 2015 and 2020, respectively. He is currently a lecturer in the School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China. His research interests include array signal processing, satellite-based navigation antijamming and measurements.
Changdi Liu
Changdi Liu is currently working toward the B.S. degree in the School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China. His research interests include array signal processing, satellite-based navigation antijamming and measurements.
Shijian Dong
Shijian Dong received the B.Sc. degree and the M.Sc. degrees from the Northeastern University, Shenyang, China, in 2011 and 2013, respectively. He received the Ph.D. degree in control theory and control engineering from the Dalian University of Technology, Dalian, China, in 2018. He is currently an associate professor in the School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China. His research interests include system modeling and control.
Xiasheng Shi
Xiasheng Shi received his B.S. degree in the School of Electrical Engineering and Automation from Hefei University of Technology, China, in 2014 and the Ph.D. degree in the College of Electrical Engineering, Zhejiang University, China, in 2020. He is currently a lecturer with the School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China. His research interests include distributed optimization, control, and estimation.