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洪泽坤,徐艳云,黄伟庆,李婷婷,于超.基于功率谱熵的隐蔽通信信号检测技术研究[J].信息安全学报,2026,11(3):262-277 [点击复制]
- HONG Zekun,XU Yanyun,HUANG Weiqing,LI Tingting,YU Chao.Research on Covert Communication Signal Detection Technology Based on Power Spectrum Entropy[J].Journal of Cyber Security,2026,11(3):262-277 [点击复制]
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| 基于功率谱熵的隐蔽通信信号检测技术研究 |
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洪泽坤1,2, 徐艳云1,2, 黄伟庆1,2, 李婷婷1,2, 于超1,2
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| (1.中国科学院信息工程研究所 北京 中国 100093;2.中国科学院大学网络空间安全学院 北京 中国 100049) |
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| 摘要: |
| 作为国家的战略资源,对电磁频谱进行有效的监测是保障电磁空间安全的重要环节。在复杂电磁环境下,低功率隐蔽通信信号的检测率低,存在潜在的电磁空间安全风险。针对这一问题,本文提出了一种基于频域功率谱熵的双门限隐蔽通信信号检测算法。在信息熵检测模型的理论基础上,该算法利用信号功率谱的信息熵作为检验统计量,针对传统单一门限检测方法在低信噪比下性能下降这一问题,设计了改进后的双判决门限,实现了在强干扰和低信噪比下对隐蔽的低功率微弱信号的盲检测。仿真和实测结果表明,在接收信噪比SNR=-10dB时,信号的检测率大于90%,优于其他传统算法,显著提升了隐蔽通信信号的检测率,同时该算法也具有抗噪声不确定性的鲁棒性。针对复杂电磁环境下的非合作频谱检测场景,基于该算法,本文提出了基于频谱迹线的分阶段功率谱熵检测方法,实现对大带宽内隐蔽通信信号个数和占用频段的估计。利用矢量信号源和USRP软件无线电平台产生若干不同调制类型的宽带信号和窄带信号,作为信息传输的隐蔽通信信号,以模拟实际环境下的宽带频谱感知场景。实测实验结果表明,该方法能在宽带范围内准确估计信号个数和占用频段,在SNR=-5dB时,准确率大于80%。 |
| 关键词: 电磁空间安全 微弱信号检测 隐蔽通信 信息熵 频谱感知 频谱监测 |
| DOI：10.19363/J.cnki.cn10-1380/tn.2026.05.18 |
| 投稿时间：2021-03-15修订日期：2021-04-23 |
| 基金项目:本课题得到中国科学院战略性先导科技专项(No.XDC02040300)资助。 |
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| Research on Covert Communication Signal Detection Technology Based on Power Spectrum Entropy |
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HONG Zekun1,2, XU Yanyun1,2, HUANG Weiqing1,2, LI Tingting1,2, YU Chao1,2
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| (1.Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100093, China;2.School of Cyber Security, University of Chinese Academy of Sciences, Beijing 100049, China) |
| Abstract: |
| As a strategic resource of the country, effective monitoring of the electromagnetic spectrum is an important part of ensuring the security of electromagnetic space. In a complex electromagnetic environment, the detection rate of covert communication signals is low, which creates potential electromagnetic space security risks. Aiming at this problem, this paper proposes a double-threshold covert communication signal detection algorithm based on frequency domain power spectrum information entropy. Based on the theoretical derivation of the information entropy detection model, this algorithm uses the information entropy of the signal power spectrum as the test statistic. In order to solve the problem of the performance degradation of the traditional single-threshold detection method, an improved dual-decision threshold is designed to achieve blind detection of hidden low-power weak signals under the background of strong interference and low signal-to-noise ratio. The simulation and experimental results show that the detection rate is greater than 90% when SNR=-10dB, which is superior to other traditional algorithms, and greatly improves the detection rate of low-power covert signals. At the same time, the algorithm also has robustness to noise uncertainty. Based on this algorithm, for non-cooperative spectrum detection scenarios in complex electromagnetic environments, this paper proposes a phased frequency domain information entropy detection method based on spectrum traces to realize the estimation of the number of covert communication signals and occupied frequency bands in a large bandwidth. The vector signal source and the USRP software radio platform are used to generate several wideband signals and narrowband signals of different modulation types, which are used as covert communication signals for information transmission to simulate the wideband spectrum sensing scenario in the actual environment. Actual experimental results show that this method can accurately estimate the number of signals and occupied frequency bands within a wideband range. When SNR=-5dB, the detection accuracy is greater than 80%. |
| Key words: electromagnetic space security weak signal detection convert communication information entropy spectrum sensing spectrum monitoring |
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