Kernel-FastICA-Based Nonlinear Blind Source Separation for Anti-Jamming Satellite Communications

Satellite communication systems, as a core component of global information infrastructure, have undergone unprecedented development. However, the open nature of satellite channels renders them vulnerable to electromagnetic interference, making anti-jamming techniques a persistent research focus in t...

Full description

Saved in:
Bibliographic Details
Main Authors: Xiya Sun, Changqing Li, Jiong Li, Qi Su
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/25/12/3743
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849425625437175808
author Xiya Sun
Changqing Li
Jiong Li
Qi Su
author_facet Xiya Sun
Changqing Li
Jiong Li
Qi Su
author_sort Xiya Sun
collection DOAJ
description Satellite communication systems, as a core component of global information infrastructure, have undergone unprecedented development. However, the open nature of satellite channels renders them vulnerable to electromagnetic interference, making anti-jamming techniques a persistent research focus in this domain. Satellite transponders contain various power-sensitive components that exhibit nonlinear characteristics under interference conditions, yet conventional anti-jamming approaches typically neglect the nonlinear distortion in transponders when suppressing interference. To address this challenge, this paper proposes a kernel-method-optimized FastICA algorithm (Kernel-FastICA) that establishes a post-nonlinear mixing model to precisely characterize signal transmission and reception processes. The algorithm transforms nonlinear separation tasks into high-dimensional, linear independent-component-analysis problems through kernel learning methodology. Furthermore, we introduce a regularized pre-whitening strategy to mitigate potential ill-conditioned issues arising from dimensional expansion, thereby enhancing numerical stability and separation performance. The simulation results demonstrate that the proposed algorithm exhibits superior robustness against interference and enhanced generalization capabilities in nonlinear jamming environments compared with existing solutions.
format Article
id doaj-art-b30a88b4ccca43a09c446f0c54fda48d
institution Kabale University
issn 1424-8220
language English
publishDate 2025-06-01
publisher MDPI AG
record_format Article
series Sensors
spelling doaj-art-b30a88b4ccca43a09c446f0c54fda48d2025-08-20T03:29:43ZengMDPI AGSensors1424-82202025-06-012512374310.3390/s25123743Kernel-FastICA-Based Nonlinear Blind Source Separation for Anti-Jamming Satellite CommunicationsXiya Sun0Changqing Li1Jiong Li2Qi Su3Graduate School, Space Engineering University, Beijing 101416, ChinaSchool of Space Information, Space Engineering University, Beijing 101416, ChinaSchool of Space Information, Space Engineering University, Beijing 101416, ChinaSchool of Space Information, Space Engineering University, Beijing 101416, ChinaSatellite communication systems, as a core component of global information infrastructure, have undergone unprecedented development. However, the open nature of satellite channels renders them vulnerable to electromagnetic interference, making anti-jamming techniques a persistent research focus in this domain. Satellite transponders contain various power-sensitive components that exhibit nonlinear characteristics under interference conditions, yet conventional anti-jamming approaches typically neglect the nonlinear distortion in transponders when suppressing interference. To address this challenge, this paper proposes a kernel-method-optimized FastICA algorithm (Kernel-FastICA) that establishes a post-nonlinear mixing model to precisely characterize signal transmission and reception processes. The algorithm transforms nonlinear separation tasks into high-dimensional, linear independent-component-analysis problems through kernel learning methodology. Furthermore, we introduce a regularized pre-whitening strategy to mitigate potential ill-conditioned issues arising from dimensional expansion, thereby enhancing numerical stability and separation performance. The simulation results demonstrate that the proposed algorithm exhibits superior robustness against interference and enhanced generalization capabilities in nonlinear jamming environments compared with existing solutions.https://www.mdpi.com/1424-8220/25/12/3743Kernel-FastICAnonlinear blind source separationsatellite communication anti-jamminginterference suppression
spellingShingle Xiya Sun
Changqing Li
Jiong Li
Qi Su
Kernel-FastICA-Based Nonlinear Blind Source Separation for Anti-Jamming Satellite Communications
Sensors
Kernel-FastICA
nonlinear blind source separation
satellite communication anti-jamming
interference suppression
title Kernel-FastICA-Based Nonlinear Blind Source Separation for Anti-Jamming Satellite Communications
title_full Kernel-FastICA-Based Nonlinear Blind Source Separation for Anti-Jamming Satellite Communications
title_fullStr Kernel-FastICA-Based Nonlinear Blind Source Separation for Anti-Jamming Satellite Communications
title_full_unstemmed Kernel-FastICA-Based Nonlinear Blind Source Separation for Anti-Jamming Satellite Communications
title_short Kernel-FastICA-Based Nonlinear Blind Source Separation for Anti-Jamming Satellite Communications
title_sort kernel fastica based nonlinear blind source separation for anti jamming satellite communications
topic Kernel-FastICA
nonlinear blind source separation
satellite communication anti-jamming
interference suppression
url https://www.mdpi.com/1424-8220/25/12/3743
work_keys_str_mv AT xiyasun kernelfasticabasednonlinearblindsourceseparationforantijammingsatellitecommunications
AT changqingli kernelfasticabasednonlinearblindsourceseparationforantijammingsatellitecommunications
AT jiongli kernelfasticabasednonlinearblindsourceseparationforantijammingsatellitecommunications
AT qisu kernelfasticabasednonlinearblindsourceseparationforantijammingsatellitecommunications