基于SVM的干扰样式选择

Jamming style selection based on SVM

建立了空-空对抗场景机载多功能火控雷达小样本干扰规则库,针对当前雷达干扰样式选择实时性及正确率不能满足认知电子战多功能雷达干扰需求问题,提出一种基于小样本干扰规则库的干扰样式选择模型及适用于该模型的支持向量机(SVM)干扰样式选择方法。将SVM理论应用干扰样式选择,利用非线性映射将输入测试数据的内积变换到特征空间的内积,其出色的学习及泛化能力,较好地解决了小样本、非线性实际问题,仿真实验验证了该方法的有效性。

A small sample jamming rule base for airborne multi-function fire control radar in air-to-air confrontation scene is established.For the problem that the radar jamming style selection real-time and correct rate cannot meet the multi-function radar jamming demand of cognitive electronic warfare.The jamming style selection model based on the jamming rule base and the support vector machine（SVM）jamming style selection method applicable to the model are proposed.The SVM theory is applied to the jamming style selection,and the inner product of the input test data is transformed into the inner product of the feature space by using the nonlinear mapping.The small sample and nonlinear practical problems are solved for its excellent learning and generalization ability.Simulate experiments verify the effectiveness of the method.