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计算机工程 ›› 2024, Vol. 50 ›› Issue (6): 65-76. doi: 10.19678/j.issn.1000-3428.0069649

• 热点与综述 • 上一篇    下一篇

卫星MIMO通信系统抗移动无人机集群干扰的在线BSS算法

秦媛1, 张杭1, 朱宏鹏1, 李炯2, 胡航3   

  1. 1. 陆军工程大学通信工程学院, 江苏 南京 210007;
    2. 航天工程大学航天信息学院, 北京 101400;
    3. 空军工程大学信息与导航学院, 陕西 西安 710077
  • 收稿日期:2024-03-25 修回日期:2024-05-08 发布日期:2024-06-11
  • 通讯作者: 朱宏鹏,E-mail:zhuhongpeng_aeu@126.com E-mail:zhuhongpeng_aeu@126.com
  • 基金资助:
    国家自然科学基金(62001516);陕西省自然科学基础研究计划项目(2024JC-YBMS-514)。

Online BSS Algorithm for Anti-jamming of Mobile UAV Cluster in Satellite MIMO Communication System

QIN Yuan1, ZHANG Hang1, ZHU Hongpeng1, LI Jiong2, HU Hang3   

  1. 1. College of Communications Engineering, Army Engineering University, Nanjing 210007, Jiangsu, China;
    2. School of Space Information, Space Engineering University, Beijing 101400, China;
    3. Information and Navigation College, Air Force Engineering University, Xi'an 710077, Shaanxi, China
  • Received:2024-03-25 Revised:2024-05-08 Published:2024-06-11

摘要: 移动无人机(UAV)集群可以对卫星多输入多输出(MIMO)通信系统下行链路近距离实施压制式恶意干扰,导致接收信号的信干比(SIR)很低,严重影响通信质量。由于移动无人机信号的传输具有快衰落特性,因此此类扰信混合不仅具有时变性,而且存在突变性。采用盲源分离(BBS)算法实现扰信分离,提出一种部分回溯自适应变步长动量项等变自适应盲分离(PR-V-M-EASI)算法。算法以自适应变步长动量项EASI算法为基础,将串音误差作为分离性能指标自适应调整步长和动量项因子,加快算法的迭代速度,以适应混合矩阵的时变性。此外,算法还通过部分回溯分离的方式提升混合矩阵突变阶段的分离性能,降低分离算法的复杂度。仿真结果表明, PR-V-M-EASI算法能够在不影响收敛速度的前提下改善混合矩阵突变导致的分离精度下降,可有效对抗移动无人机集群施放的强恶意干扰。

关键词: 卫星多输入多输出系统, 无人机集群干扰, 等变自适应盲分离, 动量项, 部分回溯, 变步长

Abstract: Mobile Unmanned Aerial Vehicle(UAV) clusters can exert suppressive malicious interference on the downlink of satellite Multiple Input Multiple Output(MIMO) communication systems at close range. This results in a low Signal-to-Interference Ratio(SIR) of received signals, thereby seriously affecting their communication quality. Due to the fast-fading characteristics of mobile UAV signal transmission, this type of interference is not only time-varying but also mutational. In this study, a Blind Source Separation(BSS) algorithm is used to separate interference from the signal. Based on the variable-step and momentum term Equivariant Adaptive Separation via Independence(EASI) algorithm, the Partial Retrospective Variable-step and Momentum factor EASI(PR-V-M-EASI) algorithm is proposed. It utilizes crosstalk error as the separation performance index to adaptively adjust the step size and momentum factor, thereby accelerating the iteration speed of the algorithm to accommodate the time variability of the mixing matrix. In addition, this algorithm enhances the separation performance during mutation stages of the mixing matrix and reduces the complexity through partial retrospective separation. Simulation results show that the proposed PR-V-M-EASI algorithm not only maintains convergence speed but also improves the separation performance degradation caused by mixing matrix mutations, effectively resisting strong malicious interference from mobile UAV clusters.

Key words: satellite Multiple Input Multiple Output(MIMO) system, jamming of Unmanned Aerial Vehicle(UAV) cluster, Equivariant Adaptive Separation via Independence(EASI), momentum term, partial retrospective, variable step size

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