{"title":"基于多种群进化策略的正交编码信号群优化","authors":"Wang Jing, Luo Feng, Wu Shunjun, Fu Shaofeng","doi":"10.1109/YCICT.2009.5382446","DOIUrl":null,"url":null,"abstract":"An improved genetic algorithm based on multiple population evolving is presented and applied to the optimization of orthogonal coded signal group for MIMO radar systems. According to the fitness of individuals, the population is divided into three groups and different evolving strategies are applied to every sub-population. The inosculation to all sub-population is actualized. This algorithm can strengthen and preserve the diversity of population. Meanwhile it can enhance the constringency speed and overcome the precocity of GA. Simulation results show that the improved genetic algorithm is effective and the optimized signal can used in MIMO radar.","PeriodicalId":138803,"journal":{"name":"2009 IEEE Youth Conference on Information, Computing and Telecommunication","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"The optimization of orthogonal coded signal group based on multiple population evolving strategies\",\"authors\":\"Wang Jing, Luo Feng, Wu Shunjun, Fu Shaofeng\",\"doi\":\"10.1109/YCICT.2009.5382446\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An improved genetic algorithm based on multiple population evolving is presented and applied to the optimization of orthogonal coded signal group for MIMO radar systems. According to the fitness of individuals, the population is divided into three groups and different evolving strategies are applied to every sub-population. The inosculation to all sub-population is actualized. This algorithm can strengthen and preserve the diversity of population. Meanwhile it can enhance the constringency speed and overcome the precocity of GA. Simulation results show that the improved genetic algorithm is effective and the optimized signal can used in MIMO radar.\",\"PeriodicalId\":138803,\"journal\":{\"name\":\"2009 IEEE Youth Conference on Information, Computing and Telecommunication\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE Youth Conference on Information, Computing and Telecommunication\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/YCICT.2009.5382446\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE Youth Conference on Information, Computing and Telecommunication","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/YCICT.2009.5382446","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The optimization of orthogonal coded signal group based on multiple population evolving strategies
An improved genetic algorithm based on multiple population evolving is presented and applied to the optimization of orthogonal coded signal group for MIMO radar systems. According to the fitness of individuals, the population is divided into three groups and different evolving strategies are applied to every sub-population. The inosculation to all sub-population is actualized. This algorithm can strengthen and preserve the diversity of population. Meanwhile it can enhance the constringency speed and overcome the precocity of GA. Simulation results show that the improved genetic algorithm is effective and the optimized signal can used in MIMO radar.
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