{"title":"RADAR Emitter Classification with Optimal Transport Distances","authors":"Manon Mottier, G. Chardon, F. Pascal","doi":"10.23919/eusipco55093.2022.9909967","DOIUrl":null,"url":null,"abstract":"Identifying unknown RADAR emitters from re-ceived pulses is an important problem in electronic intelligence. It is a difficult problem, as agile RADAR emitters can have complex characteristics, and measurements are corrupted by various noises (non-Gaussian noise, missing pulses, etc.). In this paper, we introduce a new classification method based on optimal transport distances between collected RADAR pulses and a priori known emitter classes. Compared to previously proposed methods, this method does not require a training step, it can deal with a large number of classes, and it is easily interpretable. The method is tested on data obtained by a realistic RADAR scene simulator.","PeriodicalId":231263,"journal":{"name":"2022 30th European Signal Processing Conference (EUSIPCO)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 30th European Signal Processing Conference (EUSIPCO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/eusipco55093.2022.9909967","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Identifying unknown RADAR emitters from re-ceived pulses is an important problem in electronic intelligence. It is a difficult problem, as agile RADAR emitters can have complex characteristics, and measurements are corrupted by various noises (non-Gaussian noise, missing pulses, etc.). In this paper, we introduce a new classification method based on optimal transport distances between collected RADAR pulses and a priori known emitter classes. Compared to previously proposed methods, this method does not require a training step, it can deal with a large number of classes, and it is easily interpretable. The method is tested on data obtained by a realistic RADAR scene simulator.