{"title":"基于智能算法的阵列天线方向图合成方法","authors":"Zhang He, Z. Hua, L. Hongmei, Liu Beijia, Wu Qun","doi":"10.1109/ICEICT.2016.7879764","DOIUrl":null,"url":null,"abstract":"The paper introduced the basic theories of intelligent algorithms, equally spaced linear antenna array and antenna pattern synthesis principle, also introduced the related omni-directional antenna. The procedure, parameter settings, characteristics of genetic algorithm and the neural network algorithms were demonstrated that used in the pattern synthesis, then the simulation programs were given. In the experimental stage, three groups of three different DOA of interference signal were applied to the antenna array model, respectively. The genetic algorithm and neural network algorithm were applied to the array pattern that simulated, then the simulation results were statisticed to compare their accuracy and robustness. At the same time, the linear antenna array model was established by the FEKO simulation software, whose antenna element is omni-directional COCO antenna whose center frequency is 1.8GHz. The weight coefficient produced by genetic algorithm and neural network algorithm were applied to the excitation voltage of every array elements, whose amplitude and phase is controlled by the weight coefficient. Then the results were analyzed which came from the two intelligent algorithms with different interference signals.","PeriodicalId":224387,"journal":{"name":"2016 IEEE International Conference on Electronic Information and Communication Technology (ICEICT)","volume":"68 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Array antenna pattern synthesis method based on intelligent algorithm\",\"authors\":\"Zhang He, Z. Hua, L. Hongmei, Liu Beijia, Wu Qun\",\"doi\":\"10.1109/ICEICT.2016.7879764\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper introduced the basic theories of intelligent algorithms, equally spaced linear antenna array and antenna pattern synthesis principle, also introduced the related omni-directional antenna. The procedure, parameter settings, characteristics of genetic algorithm and the neural network algorithms were demonstrated that used in the pattern synthesis, then the simulation programs were given. In the experimental stage, three groups of three different DOA of interference signal were applied to the antenna array model, respectively. The genetic algorithm and neural network algorithm were applied to the array pattern that simulated, then the simulation results were statisticed to compare their accuracy and robustness. At the same time, the linear antenna array model was established by the FEKO simulation software, whose antenna element is omni-directional COCO antenna whose center frequency is 1.8GHz. The weight coefficient produced by genetic algorithm and neural network algorithm were applied to the excitation voltage of every array elements, whose amplitude and phase is controlled by the weight coefficient. Then the results were analyzed which came from the two intelligent algorithms with different interference signals.\",\"PeriodicalId\":224387,\"journal\":{\"name\":\"2016 IEEE International Conference on Electronic Information and Communication Technology (ICEICT)\",\"volume\":\"68 1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE International Conference on Electronic Information and Communication Technology (ICEICT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEICT.2016.7879764\",\"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 IEEE International Conference on Electronic Information and Communication Technology (ICEICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEICT.2016.7879764","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Array antenna pattern synthesis method based on intelligent algorithm
The paper introduced the basic theories of intelligent algorithms, equally spaced linear antenna array and antenna pattern synthesis principle, also introduced the related omni-directional antenna. The procedure, parameter settings, characteristics of genetic algorithm and the neural network algorithms were demonstrated that used in the pattern synthesis, then the simulation programs were given. In the experimental stage, three groups of three different DOA of interference signal were applied to the antenna array model, respectively. The genetic algorithm and neural network algorithm were applied to the array pattern that simulated, then the simulation results were statisticed to compare their accuracy and robustness. At the same time, the linear antenna array model was established by the FEKO simulation software, whose antenna element is omni-directional COCO antenna whose center frequency is 1.8GHz. The weight coefficient produced by genetic algorithm and neural network algorithm were applied to the excitation voltage of every array elements, whose amplitude and phase is controlled by the weight coefficient. Then the results were analyzed which came from the two intelligent algorithms with different interference signals.