针对通信系统中通信信号线性混叠问题，提出2种基于奇异值分解的盲源提取算法。在有噪声的环境中，方法1先利用鲸鱼优化算法和主分量分析实现盲信号的逐一提取，对所提取信号逐一进行基于奇异值分解的去噪处理，得到更为纯净的信号；方法2先对观测信号进行奇异值分解去除噪声分量，再利用鲸鱼算法和主分量分析实现对盲信号的逐一提取。经过计算机仿真实验，验证了2种算法的可行性，能在有噪环境实现线性混叠信号提取和分离，并实现分离信号的去噪。结果表明，方法2比方法1更为有效，具有一定的实际应用意义。
Aiming at the problem of linear aliasing signals in communication systems, two blind source extraction algorithms based on singular value decomposition are proposed.In an environment existing noise, the first method uses the whale optimization algorithm and principal component analysis to realize the one-by-one extraction of blind signals, and uses singular value decomposition on the extracted signals one by one to obtain a pure signal;The second method is to perform singular value decomposition on the observed signal to remove components of noise, and then use whale algorithm and principal component analysis to realize the extraction of blind signals.Through computer simulation experiments, the feasibility of the two algorithms is verified, which can achieve linear aliasing signal extraction and separation in a noisy environment, and achieve denoising of the separated signals.And the second method is more effective than the first method, and has certain practical application significance.
2021,43(10): 153-157 收稿日期：2020-06-23
DOI：10.3404/j.issn.1672-7649.2021.10.031
分类号：TN956;O221.6
基金项目：国家自然科学基金资助项目(61803379)
作者简介：刘裕侃(1995-),男,硕士研究生,研究方向为通信对抗
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