{"title":"基于进化算法的最大似然函数方向估计方法","authors":"Qiang Yong, Wu Lili, Jiao Licheng","doi":"10.1109/ICCIMA.2003.1238095","DOIUrl":null,"url":null,"abstract":"A maximum likelihood method based on evolutionary algorithms (EA) is presented to estimate the direction of arrival (DOA) of coherent signals. For the capability of fast global searching, and independence of initial parameters, this approach offers real time, high resolution in DOA estimation. Simulation results show its efficiency and robust.","PeriodicalId":385362,"journal":{"name":"Proceedings Fifth International Conference on Computational Intelligence and Multimedia Applications. ICCIMA 2003","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A maximum likelihood function approach to direction estimation based on evolutionary algorithms\",\"authors\":\"Qiang Yong, Wu Lili, Jiao Licheng\",\"doi\":\"10.1109/ICCIMA.2003.1238095\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A maximum likelihood method based on evolutionary algorithms (EA) is presented to estimate the direction of arrival (DOA) of coherent signals. For the capability of fast global searching, and independence of initial parameters, this approach offers real time, high resolution in DOA estimation. Simulation results show its efficiency and robust.\",\"PeriodicalId\":385362,\"journal\":{\"name\":\"Proceedings Fifth International Conference on Computational Intelligence and Multimedia Applications. ICCIMA 2003\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-09-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings Fifth International Conference on Computational Intelligence and Multimedia Applications. ICCIMA 2003\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCIMA.2003.1238095\",\"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 Fifth International Conference on Computational Intelligence and Multimedia Applications. ICCIMA 2003","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIMA.2003.1238095","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A maximum likelihood function approach to direction estimation based on evolutionary algorithms
A maximum likelihood method based on evolutionary algorithms (EA) is presented to estimate the direction of arrival (DOA) of coherent signals. For the capability of fast global searching, and independence of initial parameters, this approach offers real time, high resolution in DOA estimation. Simulation results show its efficiency and robust.