基于支持向量回归的均匀阵波束形成框架体系研究(英文) |
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摘 要: |
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收稿时间: | 17 March 2010 |
Research on uniform array beamforming based on support vector regression |
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Authors: | Guan-cheng Lin Ya-an Li Bei-li Jin |
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Institution: | (1) School of Computer Science and Technology, Nanjing University of Science and Technology, 210094 Nanjing, People’s Republic of China;(2) School of Computer Science and Telecommunication Engineering, Jiangsu University, 212013 Zhenjiang, People’s Republic of China |
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Abstract: | An approach was proposed for optimizing beamforming that was based on Support Vector Regression (SVR). After studying the
mathematical principal of the SVR algorithm and its primal cost function, the modified cost function was first applied to
uniform array beamforming, and then the corresponding parameters of the beamforming were optimized. The framework of SVR uniform
array beamforming was then established. Simulation results show that SVR beamforming can not only approximate the performance
of conventional beamforming in the area without noise and with small data sets, but also improve the generalization ability
and reduce the computation burden. Also, the side lobe level of both linear and circular arrays by the SVR algorithm is improved
sharply through comparison with the conventional one. SVR beamforming is superior to the conventional method in both linear
and circular arrays, under single source or double non-coherent sources. |
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