| Summary: | To solve the problem of the low rate of template matching (TM) jamming decision method under the incomplete jamming rule library condition in traditional electronic warfare, a clustering and resampling – support vector machine (CRS-SVM) jamming decision method, is proposed. For the air-to-air scene of airborne multifunctional fire control radar, the inter-pulse pulse and intra-pulse features are extracted, and a jamming rule library that is divided into the source domain and target domain sample according to the missing rate is constructed in this scene. DBSCAN algorithm is used to cluster the dataset, and the structure information is found. The training samples are generated via resampling. SVM is used to transform the inner product of the target domain space into the inner product of the feature space to establish the feature space hyperplane. The target domain samples are labelled as the corresponding jamming style label to realise the fast and effective decision. The experiment results show that the proposed method can effectively improve the accuracy and robustness of jamming decision compared with the traditional TM method.
|
|---|
