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正确的干扰识别是采取有效抗干扰措施的前提和基础,文中针对间歇采样转发干扰的识别问题,提出了一种基于频谱相像系数和支持向量机的干扰识别方法。通过对目标回波及干扰信号的模型及频谱进行分析,挖掘回波与干扰信号频域上的差异,提取频谱相像系数特征,并利用支持向量机进行分类识别。仿真结果表明:相像系数特征参数类间分离度好、不易受噪声及实验次数影响,将其作为干扰识别的特征参数,得到的识别准确率较高,可以为后续雷达系统采取针对性抗干扰措施提供重要的决策信息。
Correct interference identification is the prerequisite and basis for taking effective anti-interference measures. In this paper, aiming at the problem of intermittent sampling-and-forward interference identification, a new interference identification method based on spectrum similarity coefficient and support vector machine is proposed. By analyzing the model and frequency spectrum of the target echo and interference signal, the difference between the echo and the interference signal in the frequency domain was excavated, and the spectral similarity coefficient feature was extracted and classified by using support vector machine. The simulation results show that the similarity coefficients have good separation between the characteristic parameters and are not easily affected by the noise and the number of experiments. As a characteristic parameter of the interference identification, the recognition accuracy is high, and the pertinent anti-interference measures can be taken for the subsequent radar systems Provide important decision information.