摘要
本文提出一种基于分数阶傅里叶域阵列平均的盲信号分离方法,它在变换域中引入加权函数来降低噪声及减少各源信号间的相互干扰。和传统盲信号分离方法相比,该方法不需要矩阵的白化和联合对角化,并且复杂度低,运算量小,抗干扰性能好。
A novel blind source separation method was proposed based on array average in the fractional Fourier domain,which introduces a set of weighting function into the fractional Fourier domain to decrease the noise level and interaction among the source signals.Compared with the traditional blind source separation method,the proposed method does not require whitening and joint-diagonalization to the hybrid matrix,has lower complexity,small amount of operation and good anti-jamming capability.
出处
《兵工学报》
EI
CAS
CSCD
北大核心
2009年第11期1451-1456,共6页
Acta Armamentarii
基金
国家杰出青年科学基金项目(60625104)
国家自然科学基金项目(60902054)
‘泰山学者’建设工程项目
关键词
信息处理技术
盲信号分离
阵列平均
分数阶傅里叶变换
information processing
blind source separation
array average
fractional Fourier transform
