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作 者:XIE Jianping WANG Rui HE Xiongxiong LI Sheng
机构地区:[1]Lishui University [2]Zhejiang University of Technology
出 处:《Chinese Journal of Acoustics》2017年第1期87-101,共15页声学学报(英文版)
基 金:supported by the National Science&Technology Pillar Program(2013BAF07B03);Zhejiang Provincial Natural Science Foundation of China(LY13F010009)
摘 要:An adaptive beamforming algorithm named robust joint iterative optimizationdirection adaptive (RJIO-DA) is proposed for large-array scenarios. Based on the framework of minimum variance distortionless response (MVDR), the proposed algorithm jointly updates a transforming matrix and a reduced-rank filter. Each column of the transforming matrix is treated as an independent direction vector and updates the weight values of each dimension within a subspace. In addition, the direction vector rotation improves the performance of the algorithm by reducing the uncertainties due to the direction error. Simulation results show that the RJIO-DA algorithm has lower complexity and faster convergence than other conventional reduced-rank algorithms.An adaptive beamforming algorithm named robust joint iterative optimizationdirection adaptive (RJIO-DA) is proposed for large-array scenarios. Based on the framework of minimum variance distortionless response (MVDR), the proposed algorithm jointly updates a transforming matrix and a reduced-rank filter. Each column of the transforming matrix is treated as an independent direction vector and updates the weight values of each dimension within a subspace. In addition, the direction vector rotation improves the performance of the algorithm by reducing the uncertainties due to the direction error. Simulation results show that the RJIO-DA algorithm has lower complexity and faster convergence than other conventional reduced-rank algorithms.
关 键 词:SINR DA MVDR RLS An adaptive beamforming algorithm based on direction vector rotation and joint iterative optimization
分 类 号:TN713[电子电信—电路与系统]
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