{"title":"基于深度神经网络的雷达信号识别","authors":"J. Matuszewski, Dymitr Pietrow","doi":"10.1109/PICST54195.2021.9772169","DOIUrl":null,"url":null,"abstract":"The article presents the problem of recognizing radar sources using multilayer artificial neural networks on the basis of radar parameters such as pulse repetition interval, pulse duration, radio frequency, and inter-pulse temporal structure of signals generated by these sources. Parameters of real radar signals were used as a set of training data. The correctness of the operation was tested using a simulation environment that verified the effectiveness of operation in the conditions of the presence of many radar signals that interfere with each other and in the environment of noise and interferences.","PeriodicalId":391592,"journal":{"name":"2021 IEEE 8th International Conference on Problems of Infocommunications, Science and Technology (PIC S&T)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Radar Signal Recognition Based on Deep Neural Networks\",\"authors\":\"J. Matuszewski, Dymitr Pietrow\",\"doi\":\"10.1109/PICST54195.2021.9772169\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The article presents the problem of recognizing radar sources using multilayer artificial neural networks on the basis of radar parameters such as pulse repetition interval, pulse duration, radio frequency, and inter-pulse temporal structure of signals generated by these sources. Parameters of real radar signals were used as a set of training data. The correctness of the operation was tested using a simulation environment that verified the effectiveness of operation in the conditions of the presence of many radar signals that interfere with each other and in the environment of noise and interferences.\",\"PeriodicalId\":391592,\"journal\":{\"name\":\"2021 IEEE 8th International Conference on Problems of Infocommunications, Science and Technology (PIC S&T)\",\"volume\":\"61 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-10-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 8th International Conference on Problems of Infocommunications, Science and Technology (PIC S&T)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PICST54195.2021.9772169\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 8th International Conference on Problems of Infocommunications, Science and Technology (PIC S&T)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PICST54195.2021.9772169","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Radar Signal Recognition Based on Deep Neural Networks
The article presents the problem of recognizing radar sources using multilayer artificial neural networks on the basis of radar parameters such as pulse repetition interval, pulse duration, radio frequency, and inter-pulse temporal structure of signals generated by these sources. Parameters of real radar signals were used as a set of training data. The correctness of the operation was tested using a simulation environment that verified the effectiveness of operation in the conditions of the presence of many radar signals that interfere with each other and in the environment of noise and interferences.