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一种新的盲波束形成器建模与仿真研究
引用本文:李洪升,赵俊渭,王峰,郭业才.一种新的盲波束形成器建模与仿真研究[J].系统仿真学报,2002,14(8):983-986.
作者姓名:李洪升  赵俊渭  王峰  郭业才
作者单位:西北工业大学声学工程研究所,西安,710072
基金项目:国防科技重点实验室基金项目(编号:2000JS23.2.1),船舶国防科技预研基金项目(编号:2000J42.2.8)。
摘    要:提出了一种新的基于高阶累积量和神经网络的盲波束形成器,并对其进行了建模与仿真研究。该波束形成器应用高阶累积量对期望信号的方向向量进行估计。采用线性规划神经网络实现盲波束形成。不但减少了对阵列流形的依赖,具有较好的 容差性,而且能有效地避免矩阵求逆运算,减小了运算量,易于用硬件实时实现。仿真实验验证了该波束形成器模型的有效性和正确性。

关 键 词:盲波束形成器  建模  仿真  高阶累积量  神经网络  信号处理
文章编号:1004-731X(2002)08-0983-04
修稿时间:2001年10月22

A New Blind Beamforming Modeling and Simulation
LI Hong-sheng,ZHAO Jun-wei,WANG Feng,GUO Ye-cai.A New Blind Beamforming Modeling and Simulation[J].Journal of System Simulation,2002,14(8):983-986.
Authors:LI Hong-sheng  ZHAO Jun-wei  WANG Feng  GUO Ye-cai
Abstract:A new blind beamformer based on higher-order cumulant and neural network is presented in this paper. Its model and simulation are studied further. In this beamformer, the higher-order cumulant is used to estimate the steering vector of the desired signal and the linear programming neural network is employed to carry out the blind optimizing beamforming. The algorithm is not very dependent on the manifold of the array and adapts to the error easily. It is able to avoid computing the inverse of a matrix so as to cut down on computing amount and be easily implemented by hardware. Simulation proves efficiency and correctness of this beamformer model.
Keywords:higher-order cumulant  neural network  blind beamformer  simulation  
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