摘要
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。
Accurate jamming recognition is the precondition and basis of valid anti-jamming system. Aiming at recognition of interrupted-sampling repeater jamming,we propose an jamming recognition scheme based on resemblance coefficient and support vector machine. Firstly,the mathematic models of signals are given. Next,we analyze the frequency spectrum of jamming signal and extract the resemblance coefficient as feature parameter. Then the support vector machine is adopted to classify the target and jamming. The simulation results show outstanding feature performance and high recognition rate so that priori information can be provided for radar system to select anti-jamming method.
出处
《现代雷达》
CSCD
北大核心
2016年第5期72-77,共6页
Modern Radar
关键词
间歇采样
干扰识别
特征提取
相像系数
支持向量机
interrupted-sampling
jamming recognition
feature extraction
resemblance coefficient
support vector machine
