{"title":"基于粒子群优化的雷达应用序列设计","authors":"Momin Jamil, H. Zepernick","doi":"10.1109/ATC.2016.7764775","DOIUrl":null,"url":null,"abstract":"Performance of polyphase sequences in radar applications can be evaluated using measures including autocorrelation function, integrated sidelobe ratio (ISLR), and peak-to-sidelobe ratio (PSLR). In this paper, we adopt particle swarm optimization to find optimal parameters of Oppermann sequences such that sequences with optimal ISLR and PSLR are generated. This class of sequences has been chosen as it allows to design for a wide range of correlation characteristics by essentially controlling three parameters. A sequence design example is provided in order to illustrate that particle swarm optimization is indeed well-suited to produce optimal sequence designs with respect to the considered performance measures.","PeriodicalId":225413,"journal":{"name":"2016 International Conference on Advanced Technologies for Communications (ATC)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Sequence design for radar applications using particle swarm optimization\",\"authors\":\"Momin Jamil, H. Zepernick\",\"doi\":\"10.1109/ATC.2016.7764775\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Performance of polyphase sequences in radar applications can be evaluated using measures including autocorrelation function, integrated sidelobe ratio (ISLR), and peak-to-sidelobe ratio (PSLR). In this paper, we adopt particle swarm optimization to find optimal parameters of Oppermann sequences such that sequences with optimal ISLR and PSLR are generated. This class of sequences has been chosen as it allows to design for a wide range of correlation characteristics by essentially controlling three parameters. A sequence design example is provided in order to illustrate that particle swarm optimization is indeed well-suited to produce optimal sequence designs with respect to the considered performance measures.\",\"PeriodicalId\":225413,\"journal\":{\"name\":\"2016 International Conference on Advanced Technologies for Communications (ATC)\",\"volume\":\"80 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 International Conference on Advanced Technologies for Communications (ATC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ATC.2016.7764775\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Advanced Technologies for Communications (ATC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ATC.2016.7764775","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sequence design for radar applications using particle swarm optimization
Performance of polyphase sequences in radar applications can be evaluated using measures including autocorrelation function, integrated sidelobe ratio (ISLR), and peak-to-sidelobe ratio (PSLR). In this paper, we adopt particle swarm optimization to find optimal parameters of Oppermann sequences such that sequences with optimal ISLR and PSLR are generated. This class of sequences has been chosen as it allows to design for a wide range of correlation characteristics by essentially controlling three parameters. A sequence design example is provided in order to illustrate that particle swarm optimization is indeed well-suited to produce optimal sequence designs with respect to the considered performance measures.