中国空间科学技术

中国空间科学技术 ›› 2026, Vol. 46 ›› Issue (1): 13-23.doi: 10.16708/j.cnki.1000-758X.2026.0006

• 面向星地融合的卫星互联网专题 • 上一篇    下一篇

面向低轨卫星的时延簇选择优化载波分离算法

张旭1,2,*，刘攀1，惠腾飞1,3，李加洪1,3   

  1. 1.中国空间技术研究院西安分院，西安710100
    2.空间微波通信全国重点实验室，西安710100
    3.西安电子科技大学，西安710071
  • 收稿日期:2025-04-03 修回日期:2025-06-18 录用日期:2025-06-25 发布日期:2026-01-09 出版日期:2026-01-30

Delay cluster selection optimization based carrier separation algorithm for LEO satellites

ZHANG Xu1,2,*，LIU Pan1，HUI Tengfei1,3，LI Jiahong1,3   

  1. 1.China Academy of Space Technology (Xi’an), Xi’an 710100, China
    2.Key Laboratory of Science and Technology on Space Microwave, Xi’an 710100, China
    3.Xidian University, Xi’an 710071, China
  • Received:2025-04-03 Revision received:2025-06-18 Accepted:2025-06-25 Online:2026-01-09 Published:2026-01-30

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摘要： 面向低轨互联网卫星系统复合干扰分析与提取处理需求，提出一种基于时延簇选择优化的二阶盲辨识抗失真载波分离算法。该算法针对传统信号检测识别算法在多重载波混叠场景下处理能力的不足，采用盲分离处理方法实现针对多源混合信号的分离与提取，解决多信号时频混叠带来的特征模糊问题。在此基础上，进一步基于二阶盲辨识分离处理架构下观测信号的相关矩阵特征，进行时延簇初始选择优化及搜索步进调整，从而有效降低联合对角化搜索范围及运算量，提升载波分离精度及收敛速度。由仿真分析可知，相较于传统二阶盲辨识算法，所提出的抗失真载波分离算法在10dB信噪比条件下，能够实现分离相关系数及残差信噪比7.89%及20.81%的性能提升，且对信号类型不敏感。在算法复杂度方面，所提出算法能够以较低的时延簇选择优化计算代价，换取联合对角化处理收敛速度的显著提升，相较于传统基于QR分解的类Jacobi联合对角化算法，在10dB信噪比条件下，所需求解迭代次数降低10.97%，运算时间性能提升0.62ms，有效降低了分离处理所需的计算复杂度及实际运算处理时间。在不影响低轨卫星正常通信的前提下，能够实现针对复合干扰信号的高精度分离和快速提取，为后续信号识别处理及抗干扰方案决策提供基础。

关键词: 低轨互联网卫星, 载波分离, 抗失真, 时延簇选择优化, 二阶盲辨识

Abstract: A delay cluster selection optimization based second-order blind identification (DCSO-SOBI) carrier separation algorithm against distortion is proposed to address the demands of complex interference analysis and extraction in low Earth orbit (LEO) internet satellite systems. Targeting the limitations of traditional signal detection and recognition algorithms in handling multi-carrier aliasing scenarios, the proposed algorithm employes blind separation techniques to achieve the separation and extraction of multi-source mixed signals, thereby resolving the feature ambiguity issues caused by time-frequency aliasing of multiple signals. Furthermore, based on the correlation matrix characteristics of the observed signals within the second-order blind identification (SOBI) separation architecture, the proposed algorithm optimizes the initial selection of delay clusters and adjusts the search step size, thereby effectively reducing the search range and computational load of joint block diagonalization (JBD) while improving carrier separation accuracy and convergence speed. Simulation results demonstrate that, compared with the traditional SOBI algorithm, the proposed algorithm exhibits insensitivity to signal types，and achieves a 7.89% improvement in separation correlation coefficient and a 20.81% improvement in residual signal-to-noise ratio (SNR) under a 10dB SNR condition. In terms of computational complexity, the proposed algorithm achieves a significant reduction in the convergence speed of JBD processing at a relatively low computational cost for delay cluster selection optimization. Compared with the Jacobi-like JBD algorithm based on QR decomposition, the required number of iterations is reduced by 10.97%, and the computation time is improved by 0.62ms under a 10dB SNR condition, thereby effectively lowering the computational complexity and processing time required for separation. Without impacting the normal communication of LEO satellites, the proposed algorithm enables highprecision separation and rapid extraction of complex interference signals, providing a foundation for subsequent signal recognition processing and anti-interference scheme decision-making.

Key words: LEO internet satellite, carrier separation, anti-distortion, delay cluster selection optimization, second-order blind identification