Ruitao Jia, Tianxian Zhang, Yuanhang Wang, Yanhong Deng, L. Kong
{"title":"一种智能距离门拉断(RGPO)干扰方法","authors":"Ruitao Jia, Tianxian Zhang, Yuanhang Wang, Yanhong Deng, L. Kong","doi":"10.1109/UCET51115.2020.9205386","DOIUrl":null,"url":null,"abstract":"In this paper, considering a range gate pull-off (RGPO) jamming for self-defense jamming, an optimal multiframe RGPO jamming strategy is investigated with unknown environment model. The optimal RGPO jamming strategy problem is solved by proposing a multi-frame RGPO jamming strategy optimization method based on black-box optimization technique. Firstly, we construct a multi-frame optimization model of RGPO jamming strategy by choosing the success rate of pull-off as the objective function. Then, to improve the jamming performance, a particle swarm optimization(PSO) algorithm based on Monte Carlo prediction fitness function(MC-PSO) is proposed. Finally, numerical simulation results are provided to verify the validity of the proposed method.","PeriodicalId":163493,"journal":{"name":"2020 International Conference on UK-China Emerging Technologies (UCET)","volume":"131 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"An Intelligent Range Gate Pull-off (RGPO) Jamming Method\",\"authors\":\"Ruitao Jia, Tianxian Zhang, Yuanhang Wang, Yanhong Deng, L. Kong\",\"doi\":\"10.1109/UCET51115.2020.9205386\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, considering a range gate pull-off (RGPO) jamming for self-defense jamming, an optimal multiframe RGPO jamming strategy is investigated with unknown environment model. The optimal RGPO jamming strategy problem is solved by proposing a multi-frame RGPO jamming strategy optimization method based on black-box optimization technique. Firstly, we construct a multi-frame optimization model of RGPO jamming strategy by choosing the success rate of pull-off as the objective function. Then, to improve the jamming performance, a particle swarm optimization(PSO) algorithm based on Monte Carlo prediction fitness function(MC-PSO) is proposed. Finally, numerical simulation results are provided to verify the validity of the proposed method.\",\"PeriodicalId\":163493,\"journal\":{\"name\":\"2020 International Conference on UK-China Emerging Technologies (UCET)\",\"volume\":\"131 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Conference on UK-China Emerging Technologies (UCET)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/UCET51115.2020.9205386\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on UK-China Emerging Technologies (UCET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UCET51115.2020.9205386","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Intelligent Range Gate Pull-off (RGPO) Jamming Method
In this paper, considering a range gate pull-off (RGPO) jamming for self-defense jamming, an optimal multiframe RGPO jamming strategy is investigated with unknown environment model. The optimal RGPO jamming strategy problem is solved by proposing a multi-frame RGPO jamming strategy optimization method based on black-box optimization technique. Firstly, we construct a multi-frame optimization model of RGPO jamming strategy by choosing the success rate of pull-off as the objective function. Then, to improve the jamming performance, a particle swarm optimization(PSO) algorithm based on Monte Carlo prediction fitness function(MC-PSO) is proposed. Finally, numerical simulation results are provided to verify the validity of the proposed method.