测控技术2017，Vol.36Issue(11)：14-17,22,5.
基于特征降维的卫星通信辐射源个体识别方法
Radiometric Identification for Satellite Communication Devices Based on Dimensional Reduction
贾永强 1甘露2
作者信息
- 1. 电子科技大学电子工程学院,四川成都611731
- 2. 西南电子电信技术研究所,四川成都611731
- 折叠
摘要
Abstract
A novel radiometric identification algorithm based on reconstructive dimensional reduction analysis is proposed for the applications of satellite communication security.The proposed algorithm searches the subspace which guarantees the minimum distances of intra-class feature vectors and the maximum distances of inter-class feature vectors in a supervised fashion after the extraction of the high-dimension feature vectors from all satellite devices.After the reduction of the feature vectors,the support vector machine can be trained and be used to predict the class label of an unknown device.The discriminative fingerprint features of satellite devices extracted with the proposed algorithm are linear combinations of high-dimension vectors,which reserve all the minute differences of different satellite devices.Experiments on actual data sets show the effectiveness of this algorithm for tasks of satellite devices identification.关键词
通信辐射源识别/特征降维/支持向量机Key words
radiometric identification/dimensional reduction/support vector machine分类
信息技术与安全科学引用本文复制引用
贾永强,甘露..基于特征降维的卫星通信辐射源个体识别方法[J].测控技术,2017,36(11):14-17,22,5.
