Radar Signal Recognition Based on Modified Semi-Supervised SVM Algorithm

摘要：

　　To improve the accuracy rate of radar signal recognition in increasingly sophisticated electronic countermeasure environment,a modified Semi-supervised SVM(S3VM)algorithm based on HSS(Heuristic Sampling Search)is put forward.Aiming at disadvantages of traditional semi-supervised support vector machines,the classifier constructed by modified S3VM is used for classifying the radar signal,then the recognition of tested samples are finished.Modified S3VM try to exploit multiple representative large-margin low-density separators by using HSS,it works out the shortcomings of S3VM efficiently,such as low classification accuracy rate and unstable classification performance.The experiment results show the accuracy rate is improved obviously by using the algorithm in radar signal recognition.

关键词： Semi-supervised SVM radar signal recognition Large-margin low-density separators

作者: Fu Ying Wang Xing

作者单位: Aeronautics and Astronautics Engineering College,Air Force Engineering University

会议类型: 国际会议

会议名称: 2017 IEEE 2nd Advanced Information Technology,Electronic and Automation Control Conference(IAEAC 2017)(2017 IEEE 第2届先进信息技术、电子与自动化控制国际会议)

会议地点: 重庆

会议语种:英文

页码: 2336-2340

在线出版日期: 2017-03-25（万方平台首次上网日期，不代表论文的发表时间）