In modern electronic warfare, the competition between electronic interference and anti-interference is becoming more and more fierce, which has become a hotspot in the radar countermeasure field to develop the identification algorithms for radar active jamming. This paper analyzes the radar active jamming recognition algorithm in details, and summarizes the general process of jamming identification methods in the world. Firstly, the types of common radar jamming are divided, and the jamming mechanism and the signal model of current common radar active jamming signal are introduced in details. Then from the feature-extraction means and the design of the classifiers, the flow of the jamming identification algorithm are analyzed comprehensively. Finally, the future development directions of the radar active jamming identification algorithms are prospected.
表 4 FRFT域干扰识别方法汇总Table 4 Summary of jamming recognition methods in FRFT domain
表 2 双谱域干扰识别方法汇总Table 2 Summary of jamming recognition methods in bispectrum domain
表 6 不同算法识别效果对比Table 6 Comparison of recognition performance of different algorithms
表 5 深度学习干扰识别方法汇总Table 5 Summary of deep learning based jamming recognition methods
图1 干扰识别的一般流程Fig.1 Flow of jamming recognition
图2 DRFM干扰机原理框图Fig.2 Block diagram of DRFM jammer
图3 雷达干扰的分类Fig.3 Classification of radar jamming
图4 雷达被干扰的场景图Fig.4 Scene diagram of radar being jammed
图5 LFM信号的双谱图及其对角切片Fig.5 Bispectrum and its diagonal slice diagram of LFM signal
图6 3层小波分解示意图Fig.6 Schematic diagram of three-layer wavelet decomposition
图7 LFM信号的遍历旋转角度FRFT分析Fig.7 FRFT analysis of ergodic rotation angle of LFM signal
图8 分类树算法流程图Fig.8 Flow chart of classification tree algorithm
图9 支持向量与最大间隔Fig.9 Support vector and maximum margin
图10 卷积神经网络模型图[73]Fig.10 Schematic of CNN model[73]
表 3 小波域干扰识别方法汇总Table 3 Summary of jamming recognition methods in wavelet domain