针对复杂电磁环境下雷达对干扰信号的分类识别问题, 研究了噪声干扰、密集假目标干扰、复合干扰信号的时域、频域特征, 通过对不同特征参数进行对比分析, 选取了区别度较大的参数组成识别特征向量, 构建了一种支持向量机(SVM)识别结构, 并进行了分类识别仿真分析。结果表明: 该识别结构特征参数提取简捷、运算速度快, 对噪声干扰、密集假目标干扰、组合干扰具有较高的识别概率, 具有一定的应用前景。

Aiming at the classification and recognition of radar jamming signals in complex electromagnetic environment, the time-domain and frequency-domain characteristics of noise jamming, dense false target jamming and combined jamming signals are studied. Comparison and analysis are made to different characteristic parameters, and the parameters with large difference are used to establish the identification feature vectors. Thus a Support Vector Machine (SVM) recognition structure is constructed for classification and recognition in simulation. The results show that, the feature parameters of the recognition structure are easily extracted, and the operation speed is fast, which has a high recognition probability to noise jamming, dense false target jamming and combined jamming, and has a certain application prospect.