Robust adaptive beamforming based on sparse reconstruction using a non-convex optimisation algorithm
A novel robust adaptive beamforming technique is proposed to solve the problem of performance degradation with one single snapshot. A sparse signal recovery model under the non-convex optimisation framework is first established, which dispenses with the mismatched sample covariance matrix, an indisp...
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| Vydáno v: | Electronics letters Ročník 52; číslo 19; s. 1584 - 1586 |
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| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
The Institution of Engineering and Technology
15.09.2016
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| ISSN: | 0013-5194, 1350-911X, 1350-911X |
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| Abstract | A novel robust adaptive beamforming technique is proposed to solve the problem of performance degradation with one single snapshot. A sparse signal recovery model under the non-convex optimisation framework is first established, which dispenses with the mismatched sample covariance matrix, an indispensable part of most existing beamformers. Then, an iterative algorithm is designed to solve the optimisation problem by using the p-shrinkage operator and the alternating direction method of multipliers. The iteration steps are closed form and convenient to apply in practice. Simulation results demonstrate the effectiveness and robustness of the proposed algorithm. |
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| AbstractList | A novel robust adaptive beamforming technique is proposed to solve the problem of performance degradation with one single snapshot. A sparse signal recovery model under the non-convex optimisation framework is first established, which dispenses with the mismatched sample covariance matrix, an indispensable part of most existing beamformers. Then, an iterative algorithm is designed to solve the optimisation problem by using the p-shrinkage operator and the alternating direction method of multipliers. The iteration steps are closed form and convenient to apply in practice. Simulation results demonstrate the effectiveness and robustness of the proposed algorithm. |
| Author | Liu, Chengcheng Zhao, Yongjun Chen, Pei |
| Author_xml | – sequence: 1 givenname: Pei surname: Chen fullname: Chen, Pei email: clevercpei@126.com organization: Navigation and Aerospace Target Engineering Department, National Digital Switching System Engineering and Technology Research Center, Zhengzhou 450001, People's Republic of China – sequence: 2 givenname: Yongjun surname: Zhao fullname: Zhao, Yongjun organization: Navigation and Aerospace Target Engineering Department, National Digital Switching System Engineering and Technology Research Center, Zhengzhou 450001, People's Republic of China – sequence: 3 givenname: Chengcheng surname: Liu fullname: Liu, Chengcheng organization: Navigation and Aerospace Target Engineering Department, National Digital Switching System Engineering and Technology Research Center, Zhengzhou 450001, People's Republic of China |
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| Cites_doi | 10.1109/TSP.2015.2396002 10.1109/TAP.2006.886473 10.1016/j.sigpro.2012.10.021 |
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| Copyright | The Institution of Engineering and Technology 2020 The Institution of Engineering and Technology |
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| Keywords | covariance matrices iterative methods multiplier sparse reconstruction iterative algorithm mismatched sample covariance matrix nonconvex optimisation algorithm sparse signal recovery model signal reconstruction robust adaptive beamforming technique concave programming array signal processing p-shrinkage operator |
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| References | Elnashar, A.; Elnoubi, S.M.; El-Mikati, H.A. (C1) 2006; 54 Huang, L.; Zhang, J.; Xu, X.; Ye, Z. (C4) 2015; 63 Vorobyov, S.A. (C3) 2013; 93 Yu, S.J.; Lee, J.H. (C2) 2015; 63 2013; 93 2006; 54 2015 2015; 63 e_1_2_9_6_1 e_1_2_9_5_1 e_1_2_9_4_1 e_1_2_9_2_1 Yu S.J. (e_1_2_9_3_1) 2015; 63 |
| References_xml | – volume: 63 start-page: 1643 year: 2015 end-page: 1650 ident: C4 article-title: Robust adaptive beamforming with a novel interference-plus-noise covariance matrix reconstruction method publication-title: Trans. Signal Process. – volume: 54 start-page: 3647 year: 2006 end-page: 3658 ident: C1 article-title: Further study on robust adaptive beamforming with optimum diagonal loading publication-title: Trans. Antennas Propag. – volume: 93 start-page: 3264 year: 2013 end-page: 3277 ident: C3 article-title: Principles of minimum variance robust adaptive beamforming design publication-title: Signal Process. – volume: 63 start-page: 1643 year: 2015 end-page: 1650 ident: C2 article-title: Efficient eigenspace-based array signal processing using multiple shift-invariant subarrays publication-title: Trans. Antennas Propag. – volume: 54 start-page: 3647 year: 2006 end-page: 3658 article-title: Further study on robust adaptive beamforming with optimum diagonal loading publication-title: Trans. Antennas Propag. – volume: 93 start-page: 3264 year: 2013 end-page: 3277 article-title: Principles of minimum variance robust adaptive beamforming design publication-title: Signal Process. – start-page: 1 year: 2015 end-page: 29 – volume: 63 start-page: 1643 year: 2015 end-page: 1650 article-title: Efficient eigenspace‐based array signal processing using multiple shift‐invariant subarrays publication-title: Trans. Antennas Propag. – volume: 63 start-page: 1643 year: 2015 end-page: 1650 article-title: Robust adaptive beamforming with a novel interference‐plus‐noise covariance matrix reconstruction method publication-title: Trans. Signal Process. – ident: e_1_2_9_6_1 – ident: e_1_2_9_5_1 doi: 10.1109/TSP.2015.2396002 – ident: e_1_2_9_2_1 doi: 10.1109/TAP.2006.886473 – ident: e_1_2_9_4_1 doi: 10.1016/j.sigpro.2012.10.021 – volume: 63 start-page: 1643 year: 2015 ident: e_1_2_9_3_1 article-title: Efficient eigenspace‐based array signal processing using multiple shift‐invariant subarrays publication-title: Trans. Antennas Propag. |
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| SubjectTerms | Adaptive algorithms Algorithms Antennas and propagation array signal processing Beamforming concave programming covariance matrices Electronics Exact solutions iterative algorithm iterative methods Mathematical analysis mismatched sample covariance matrix multiplier nonconvex optimisation algorithm Optimization p‐shrinkage operator robust adaptive beamforming technique Robustness signal reconstruction sparse reconstruction sparse signal recovery model |
| Title | Robust adaptive beamforming based on sparse reconstruction using a non-convex optimisation algorithm |
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