| 摘要: |
| 卫星通信系统暴露在太空中，极其容易受到干扰，特别是当遇到跟踪干扰时，会严重影响跳频卫星通信系统性能。利用跳频信号与跟踪干扰信号之间的统计独立性，将跳频通信抗跟踪干扰问题转化为一个多数据集联合盲源分离（Joint Blind Source Separation，JBSS）问题，在独立向量分析（Independent Vector Analysis，IVA）的框架下进行干扰信号抑制。该方法同时利用了各信号之间的统计独立性和每个信号内部的统计相关性，有效提高了系统性能。仿真结果表明，所提方法在干扰压制比为0.6且信噪比为15 dB的情况下，系统误码率相比基于能量相关性排序的独立成分分析（Independent Component Analysis，ICA）方法下降了12.06 dB，有效提高了卫星跳频通信系统抵抗跟踪干扰的能力。 |
| 关键词: 卫星通信 跳频通信 跟踪干扰 通信抗干扰 联合盲源分离（JBSS） 独立向量分析(IVA) |
| DOI：10.20079/j.issn.1001-893x.220525001 |
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| 基金项目:国家自然科学基金资助项目（62001516） |
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| An Anti-follower Jamming Joint Blind Source Separation Method for Frequency Hopping Communication System Based on IVA |
| FENG Lu,LI Changqing,LI Jiong,LIU Yang |
| (a.Graduate School;b.Space Information School,Space Engineering University,Beijing 101400,China) |
| Abstract: |
| Satellite communication system exposed in space is extremely vulnerable to interference,especially when it encounters follower jamming,which will seriously affect the performance of frequency hopping(FH) satellite communication system.According to the statistical independence between FH signal and follower jamming signal,the anti-follower jamming problem of FH communication is transformed into a joint blind source separation（JBSS） problem of multiple datasets,and the follower jamming signal is suppressed under the framework of independent vector analysis(IVA).This method makes use of the statistical independence between signals and the statistical correlation within each signal,which effectively improves the system performance.The simulation results show that when the interference suppression ratio is 0.6 and the signal-to-noise ratio is 15 dB,the bit error rate(BER) of the proposed method is reduced by 12.06 dB compared with the independent component analysis method based on energy correlation permutation,which effectively improves the anti-follower jamming ability of satellite FH communication system. |
| Key words: satellite communication FH communication follower jamming communication anti-jamming joint blind source separation(JBSS) independent vector analysis(IVA) |
