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弱信号环境下的盲自适应波束形成
引用本文:熊超,王建英.弱信号环境下的盲自适应波束形成[J].电子科技大学学报(社会科学版),2007(2).
作者姓名:熊超  王建英
作者单位:南京电子设备研究所,西南交通大学信息科学与技术学院 南京210007 西南交通大学信息科学与技术学院成都610031,成都610031
基金项目:国家自然科学基金资助项目(60602043),四川省应用基础研究基金资助项目(03JY029-048-2)
摘    要:针对原CCAB算法的相关矩阵对循环平稳信号不够准确而导致算法在恶劣环境下的鲁棒性不够强问题,提出一种鲁棒性更强的CCAB改进算法。推导了适合循环平稳信号阵列相关矩阵的理论式,经过分析原相关矩阵的不准确性和遗忘因子的正面作用后,得出了新相关矩阵的迭代式。仿真结果表明改进的算法能在计算量不变的情况下更有效地接收弱信号、抑制强干扰,且对循环频率误差不敏感。

关 键 词:盲波束形成  相关矩阵  循环平稳性  遗忘因子

Blind Adaptive Beamforming under Weak Signals Environments
Xiong Chao,Wang Jian-ying.Blind Adaptive Beamforming under Weak Signals Environments[J].Journal of University of Electronic Science and Technology of China(Social Sciences Edition),2007(2).
Authors:Xiong Chao    Wang Jian-ying
Institution:Xiong Chao1,2,Wang Jian-ying2
Abstract:Robustness of Constrained Cyclic Adaptive Beam-Forming (CCCAB) included in Cyclic Adaptive Beam-Forming (CAB) algorithms will become lower under bad signals environments because its correlation matrix is not very suitable for cyclostationary signals. An improved algorithm for CCAB is presented as a solution to the problem in this paper. The theoretic formula of the correlation matrix for cyclostationary signals is induced firstly, after the inexactness of the old correlation matrix and the positive effect of forgetting factor are analyzed, the recursive formula of the new correlation matrix is concluded. The comparsion of computer simulations shows that the improved algorithm can receive weak signals, depress interferences and decreace the sensitivity to cyclic frequency error more effectively.
Keywords:blind beamforming  correlation matrix  cyclostatinary  forgetting factor
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