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一种基于奇异值分解的解相干算法

Ji Zhengyan,Chen Hui,Zhang Jiajia,Li Shuai,Lu Xiaofei

JOURNAL OF ELECTRONICS & INFORMATION TECHNOLOGY（2017）

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Abstract
该文针对稀疏重构解相干问题,利用接收数据厅奇导值分解(SVD)后的大特征值对应的特征矢量,提出一种改进解相干方法.该方法通过迭代这一特征矢量来重构角度,无需知道信号源的数目,即可准确重构角度信息,实现解相干.相对于经典SVD算法,所提算法运算速度更快,稀疏重构效果更优.理论分析和仿真结果都验证了算法的良好性能.
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Key words
Signal processing,Sparse reconstruction,Decoherence,Singular Value Decomposition (SVD)
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