针对频谱弥散(SMSP)和切片组合(C&I)两种有源欺骗干扰检测识别算法计算量大，需要过采样等问题，提出了频谱弥散和切片组合欺骗式干扰的识别算法。该算法首先建立干扰的时、频域模型，在此基础上分析其时、频域特征，并进一步提取基于时域的盒维数与基于频域的指数熵作为干扰的本质特征参数，通过基于二叉树结构的支持向量机分类器(SVM)对干扰信号进行分类识别。仿真结果表明，在一定的信噪比要求下，该算法能够准确识别出干扰类型，为雷达抗干扰措施的选取提供先验知识，提高雷达在复杂电磁环境下工作的可靠性。%In order to enhance the radar operational effectiveness,a novel jamming detection and identification algorithm was proposed,in allusion to heavy calculation burden and oversampling of smeared spectrum(SMSP) and chopping and interleaving(C&I)identification.Firstly,the mathematical models of jamming signals in time and frequency domain were established and characters in time and frequency domain were analyzed.Further-more,box dimension based on magnitude spectrum and exponential entropy based on frequency spectrum were extracted as the input feature parameters.The performance of the binary tree based SVM classifier was investi-gated using these two features.The simulation results showed that the new algorithms had high accuracy in jam-ming identification.It could supply prior knowledge for anti-jamming measures choosing,and ensured reliability of radar in complex electromagnetic environment.
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