首页> 外文会议>International conference on digital image processing >Jamming Decision under Condition of Feature Incomplete Database
【24h】

Jamming Decision under Condition of Feature Incomplete Database

机译:特征不完整数据库条件下的干扰决策

获取原文

摘要

To solve the low accuracy problem of the template matching(TM) method under condition of feature incomplete database in traditional EW, a multiple division support vector machine (MD-SVM) jamming decision method is proposed. For the air-to-air scene airborne multi-functional fire control radar, a feature incomplete database is constructed. The sample set is divided into multiple sample subsets using multiple division method. The inner product of multiple sample subset spaces is transformed to the inner product of the feature space by SVM. Feature space hyperplane is established, and the jamming tags corresponding to the sample subsets are output. Then the jamming style is quickly and effectively determined. The experimental results show that the proposed method can effectively improve the accuracy and robustness of the jamming decision compared with the traditional TM and non-multiple division method. The feature incomplete database jamming decision problem is solved for its excellent learning and generalization ability.
机译:为了解决传统电子战中特征不完整的数据库模板匹配方法精度低的问题,提出了一种多分割支持向量机(MD-SVM)干扰决策方法。对于空对空机载多功能火控雷达,建立了特征不完整的数据库。使用多重划分方法将样本集划分为多个样本子集。 SVM将多个样本子空间的内积转换为特征空间的内积。建立特征空间超平面,并输出与样本子集相对应的干扰标签。然后,可以快速有效地确定干扰样式。实验结果表明,与传统的TM和非多次除法相比,该方法能够有效提高干扰决策的准确性和鲁棒性。解决了特征不完全的数据库阻塞决策问题,因为它具有出色的学习和泛化能力。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号