摘要
针对时域与频域均交叠的多路数字带通通信信号盲分离问题,利用布谷鸟搜索算法,研究了一种新的基于独立成分分析的盲分离方法。在均匀线阵下,构建混叠信号模型;从最大化信号非高斯性角度,将盲源分离问题转化为信号峭度的优化问题;利用布谷鸟搜索算法优化求解近似峭度的代价函数,将迭代产生的适应度值最高的个体作为解混向量,实现源信号的分离。与已有的基于固定点算法的独立成分分析方法相比,该方法能够克服其无法分离时频域混叠的振幅键控(ASK)信号的限制,适用于任何调制类型的数字带通通信信号盲分离。通过仿真实验验证了方法的有效性并分析了方法性能,实验结果表明在较低信噪比条件下,分离的信号具有较高信干比,说明方法具有较高的鲁棒性。
To blindly separate multiple digital band-pass communication signals which are overlapped in time and frequency domains,by using the cuckoo search algorithm,a new separation method is researched based on the independent component analysis.Firstly,the mixed signal model is constructed under uniform linear arrays.Secondly,from the perspective of maximizing the non-Gaussianity of signals,the separation of signals is transformed to the problem of optimizing kurtoses of signals.Finally,the cuckoo search algorithm is used to optimize the cost function which approximates kurtosis.The iteratively generated individuals having the best fitness is regarded as the mix-solving vector and then the source signals are separated.Compared with the existing independent component analysis methods based on fixed-point algorithms,the method in this paper is able to overcome the limitation of its inability to separate the amplitude keying(ASK)signals that are intermixed in the time-frequency domain,and it is applicable to the blind separation of digital bandpass communication signals with any modulation type.The validity of the method is verified and the performance of the method is analyzed through simulation experiments,which show that the separated signals have a high signal-to-inference under the condition of lower signal-to-noise ratio,indicating that the method has high robustness.
作者
韩树楠
陈铸龙
卢勇君
HAN Shunan;CHEN Zhulong;LU Yongjun(Aviation University of Air Force,Changchun 130000,China;PLA 93107 Troops,Shenyang 110000,China;PLA 95507 Troops,Guiyang 550000,China)
出处
《现代防御技术》
北大核心
2024年第3期87-95,共9页
Modern Defence Technology
关键词
独立成分分析
布谷鸟搜索
通信信号
时频域
混叠
盲分离
independent component analysis
cuckoo search
communication signal
time and frequency domains
overlapped
blind separation
