| 摘要: |
| 通信辐射源个体识别是目前通信对抗领域研究热点与难点问题，相对于雷达辐射源，通信辐射源信号弱、瞬时特征不明显导致个体识别更复杂、更困难。利用通信辐射源信号的长时谱统计特性，提取信号功率谱峰值特征和包络模板，构造通信辐射源个体特征向量，通过朴素贝叶斯分类算法与个体特征矢量相结合，在训练样本数目足够大的条件下可进行有效识别。测试实验表明，识别方法稳健有效，可在信噪比5 dB情况下实现93.7%的正确识别概率。 |
| 关键词: 通信对抗；通信辐射源个体识别 峰值提取 包络特征 模板匹配 模式识别 |
| DOI： |
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| 基金项目: |
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| A robust specific communication emitter identification method |
| HUANG Xin,GUO Hanwei |
| () |
| Abstract: |
| Specific communication emitter identification is a hot topic and difficult issue in the field of communications countermeasures and specific emitter idendification of communication emitter is more difficult and complex than that of radar emitter due to weaker signal and transient characteristics.In this paper, the long-time spectrum feature of specific communication emitter is used to extract the peak and envelope templates in power spectrum domain and construct the specific vector feature.Combining the Naive Bayes classifier with the specific vector feature can effectively identify the communication emitters under the condition of enough training sample number. Actual test results show that the identification method is robust and effective,with the correct recognition probability of 93.7% when signal-to-noise ratio(SNR) is 5 dB. |
| Key words: communication countermeasure specific communication emitter identification peak extraction envelope features template matching pattern recognition |
《电讯技术》编辑部 