{"title":"基于复杂网络分析的雷达工作模式识别方法","authors":"Liu Yang, Yan-Lou He, Shouye Lv, Jianfeng Ma","doi":"10.1145/3503047.3503051","DOIUrl":null,"url":null,"abstract":"Aiming at the problem that it is difficult to recognize the working mode of multi-functional radar without prior information, this paper proposes a radar working mode recognition method based on complex network analysis. Use the simulated reconnaissance data of the same type of radar to build a complex network, by analyzing the importance of network nodes, the radar phrases in search and non-search working modes are recognized. And Gephi is used as a visualization platform to show the regular features of radar phrases in different working modes. On this basis, the functional state of the radar system is analyzed by calculating the network density of the complex network.","PeriodicalId":190604,"journal":{"name":"Proceedings of the 3rd International Conference on Advanced Information Science and System","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Radar Working Mode Recognition Method Based on Complex Network Analysis\",\"authors\":\"Liu Yang, Yan-Lou He, Shouye Lv, Jianfeng Ma\",\"doi\":\"10.1145/3503047.3503051\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aiming at the problem that it is difficult to recognize the working mode of multi-functional radar without prior information, this paper proposes a radar working mode recognition method based on complex network analysis. Use the simulated reconnaissance data of the same type of radar to build a complex network, by analyzing the importance of network nodes, the radar phrases in search and non-search working modes are recognized. And Gephi is used as a visualization platform to show the regular features of radar phrases in different working modes. On this basis, the functional state of the radar system is analyzed by calculating the network density of the complex network.\",\"PeriodicalId\":190604,\"journal\":{\"name\":\"Proceedings of the 3rd International Conference on Advanced Information Science and System\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 3rd International Conference on Advanced Information Science and System\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3503047.3503051\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 3rd International Conference on Advanced Information Science and System","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3503047.3503051","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Radar Working Mode Recognition Method Based on Complex Network Analysis
Aiming at the problem that it is difficult to recognize the working mode of multi-functional radar without prior information, this paper proposes a radar working mode recognition method based on complex network analysis. Use the simulated reconnaissance data of the same type of radar to build a complex network, by analyzing the importance of network nodes, the radar phrases in search and non-search working modes are recognized. And Gephi is used as a visualization platform to show the regular features of radar phrases in different working modes. On this basis, the functional state of the radar system is analyzed by calculating the network density of the complex network.