{"title":"Key Radar Signal Sorting and Recognition Method Based on Clustering Combined PRI transform Algorithm","authors":"Kaige Kang, Yixiao Zhang, Wenpu Guo, Luogeng Tian","doi":"10.37965/jait.2022.0076","DOIUrl":null,"url":null,"abstract":"In this paper, we investigate the problem of key radar signal sorting and recognition in electronic intelligence (ELINT). Our major contribution is the development of a combined approach based on clustering and PRI transform algorithm, to solve the problem that the traditional methods based on Pulse Description Words (PDW) were not exclusively targeted at tiny particular signals and, less time-efficient. We achieve this in three steps: firstly, PDW presorting is carried out by the DBSCAN clustering algorithm, then, PRI estimates of each cluster are obtained by the PRI transformation algorithm, finally, by judging the matching between various PRI estimates and key targets, it is determined whether the current signal contains key target signals or not. Simulation results show that the proposed method should improve the time efficiency of key signal recognition and deal with the complex signal environment with noise interference and overlapping signals.","PeriodicalId":70996,"journal":{"name":"人工智能技术学报(英文)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"人工智能技术学报(英文)","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.37965/jait.2022.0076","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
In this paper, we investigate the problem of key radar signal sorting and recognition in electronic intelligence (ELINT). Our major contribution is the development of a combined approach based on clustering and PRI transform algorithm, to solve the problem that the traditional methods based on Pulse Description Words (PDW) were not exclusively targeted at tiny particular signals and, less time-efficient. We achieve this in three steps: firstly, PDW presorting is carried out by the DBSCAN clustering algorithm, then, PRI estimates of each cluster are obtained by the PRI transformation algorithm, finally, by judging the matching between various PRI estimates and key targets, it is determined whether the current signal contains key target signals or not. Simulation results show that the proposed method should improve the time efficiency of key signal recognition and deal with the complex signal environment with noise interference and overlapping signals.