| 电台类别 | 分形特征量 | ||
| Kolmogorov熵 | Lyapunov指数 | 相关维数 | |
| 电台1 | 0.5667 | 0.0312 | 3.2658 |
| 电台2 | 0.4610 | 0.1372 | 4.9878 |
| 电台3 | 0.9925 | 0.2207 | 1.4193 |
| 电台4 | 0.2919 | 0.1632 | 2.7587 |
引用本文:
眭萍, 郭英, 李红光, 王宇宙. 基于混沌吸引子重构和Low-rank聚类的跳频信号电台分选[J]. 电子与信息学报,
2019, 41(12): 2965-2971.
doi:
10.11999/JEIT180947
Citation: Ping SUI, Ying GUO, Hongguang LI, Yuzhou WANG. Frequency-hopping Transmitter Classification Based on Chaotic Attractor Reconstruction and Low-rank Clustering[J]. Journal of Electronics and Information Technology, 2019, 41(12): 2965-2971. doi: 10.11999/JEIT180947
Citation: Ping SUI, Ying GUO, Hongguang LI, Yuzhou WANG. Frequency-hopping Transmitter Classification Based on Chaotic Attractor Reconstruction and Low-rank Clustering[J]. Journal of Electronics and Information Technology, 2019, 41(12): 2965-2971. doi: 10.11999/JEIT180947
基于混沌吸引子重构和Low-rank聚类的跳频信号电台分选
摘要:
辐射源无调制信息的暂态信号能够表征辐射源发射机的无意调制特性，对该暂态信号分析可实现辐射源识别。而跳频电台在开机以及频率转换瞬间，都存在一个无信息传送的暂态调整时间，该暂态调整瞬间，电台发射的信号是无调制信息的非线性、非平稳和非高斯信号。该暂态时间序列可反映跳频电台的器件特性，同时该序列往往呈现复杂的混沌特性。因此，借鉴混沌时间序列分析的思想，同时利用暂态信号的Low-rank特性，该文提出了一种基于暂态信号混沌吸引子重构和Low-rank聚类的跳频信号电台分选算法。实验测试表明：跳频电台的暂态信号时间序列属于混沌时间序列，同时实测多跳频信号的电台分选结果证明了Low-rank聚类算法在跳频电台分选上的可行性。
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关键词:
- 跳频电台
- / 暂态信号
- / 混沌吸引子
- / Low-rank聚类
English
Frequency-hopping Transmitter Classification Based on Chaotic Attractor Reconstruction and Low-rank Clustering
Abstract:
The transient signal without modulation information of the radiation source can characterize the unintentional modulation characteristics of the radiation source. The analysis of the transient signal can realize the radiation source identification. In the switching on and frequency conversion process of the frequency-hopping signal, there is a transient adjustment time without information transmission. In the transient adjustment moment, the signal transmitted by the transmitter is a non-linear, non-stationary and non-Gaussian signal without modulation information. This transient time series can reflect the device characteristics of the frequency-hopping transmitter, and the sequence often exhibits complex chaotic characteristics. Therefore, from the idea of chaotic time series analysis and Low-rank characteristics of transient signal, a frequency-hopping transmitter classification algorithm is proposed based on chaotic attractor reconstruction and Low-rank clustering. The experimental tests show that the transient signal of the frequency-hopping transmitter belongs to the chaotic time series. At the same time, the classification results of the frequency-hopping signals demonstrate the feasibility of the Low-rank clustering algorithm in frequency-hopping transmitter classification.
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表 1 暂态信号混沌吸引子的分形特征量
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