CAJ | 학술논문

信号分离是雷达电子对抗的重要环节。考虑到雷达信号在时频域具有稀疏性的特点，在独立分量分析的基础上，提出了一种基于时频域稀疏性的线性调频雷达信号盲源分离方法。首先对混合信号进行短时傅里叶变换，在每个频点利用自然梯度算法分离信号，由分离信号幅度的比值作为对源信号后验概率的估计；然后根据相邻频点后验概率序列的相关性进行排序，确保各个频点的分离信号属于同一个源信号；最后设计时频掩码分离信号。进行了线性调频雷达信号卷积混合的盲分离实验，所提方法分离结果明显优于传统独立分量分析方法的分离结果，验证了该方法的有效性。
신호분리시뢰체전자대항적중요배절。고필도뢰체신호재시빈역구유희소성적특점，재독립분량분석적기출상，제출료일충기우시빈역희소성적선성조빈뢰체신호맹원분리방법。수선대혼합신호진행단시부리협변환，재매개빈점이용자연제도산법분리신호，유분리신호폭도적비치작위대원신호후험개솔적고계；연후근거상린빈점후험개솔서렬적상관성진행배서，학보각개빈점적분리신호속우동일개원신호；최후설계시빈엄마분리신호。진행료선성조빈뢰체신호권적혼합적맹분리실험，소제방법분리결과명현우우전통독립분량분석방법적분리결과，험증료해방법적유효성。
Signal separation is vital for radar electronic countermeasures. According to the sparseness of ra-dar signals in the time-frequency( T-F) domain,a T-F domain sparseness based linear frequency modula-tion( LFM) radar signal blind source separation( BSS) method is proposed based on the independent com-ponent analysis( ICA) method. Firstly,with the short-time Fourier transform( STFT) of the mixed signals, natural gradient algorithm is used to separate signals in each frequency bin,and the ratio of magnitudes of the separated signals is taken as the estimation of posterior probability. Secondly,the permutation ambigui-ties are aligned according to the correlations of posterior probability sequences in adjacent frequencies to ensure that the separated signal in each bin belongs to the same source. Finally,T-F mask is designed to separate signals. BSS experiments are conducted for convolutively mixed LFM radar signals and the pro-posed method’ s separation results are obviously better than those of traditional ICA method,which shows the effectiveness of the proposed method.