摘要
随着全球导航卫星系统(GNSS)在各领域的广泛应用,其面临的欺骗干扰威胁日益严峻。传统的欺骗干扰检测方法在复杂电磁环境下存在检测精度低、虚警率高等问题。本文提出了一种基于GNSS卫星信号信噪比(SNR)与主特征独立分量分析(ICA)融合的欺骗干扰检测识别算法。该算法通过SNR预筛选缩小信号处理范围,利用主特征ICA优化信号分离,并结合SNR差异实现干扰类型识别。研究表明,该融合算法在中等至高SNR环境下检测识别率可达90%以上,显著优于传统主特征ICA算法的85%。算法具有计算复杂度低、实时性好等优势,为GNSS的安全防护提供了有效技术支撑。
With the widespread application of global navigation satellite system(GNSS)in various fields,the threat posed by spoofing interference is becoming increasingly severe.Traditional spoofing interference detection methods suffer from low detection accuracy and high false alarm rates in complex electromagnetic environments.In this paper,a spoofing interference detection and identification algorithm based on the fusion of GNSS satellite signal-to-noise ratio(SNR)and principal-features independent component analysis(ICA)is proposed.The algorithm first employs SNR-based pre-screening to narrow the signal processing scope,then utilizes principal-feature ICA to optimize signal separation,and finally identifies interference types by exploiting SNR differences.The study demonstrates that the proposed fusion algorithm achieves a detection and identification rate of over 90%in medium to high SNR environments,which is significantly higher than the 85%of the traditional principal-feature ICA algorithm.The proposed algorithm has the advantages of low computational complexity and good real-time performance,providing effective technical support for the security protection of GNSS.
作者
金皓纯
屈刚
张亮
葛敏辉
JIN Haochun;QU Gang;ZHANG Liang;GE Minhui(East China Branch,State Grid Corporation of China,Shanghai 200000,China)
出处
《传感器与微系统》
北大核心
2026年第4期153-157,共5页
Transducer and Microsystem Technologies
基金
国家电网有限公司华东分部科技项目(52992425000T)。
