{"title":"基于模糊神经网络的近场测向","authors":"Ching-Wen Ma, C. Teng","doi":"10.1109/AFSS.1996.583596","DOIUrl":null,"url":null,"abstract":"The single-source near-field direction finding problem can be solved by a fuzzy neural network (FNN). The FNN approach can be applied to arrays with arbitrary configurations. It can also be implemented for real-time tracking applications. The approach outperforms the far-field approximation (FFA) approach when the array is uniformly-spaced and linear, especially when the angle between the array normal direction and the source direction is large and the distance from array center to the source is short.","PeriodicalId":197019,"journal":{"name":"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium","volume":"55 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Near-field direction finding with a fuzzy neural network\",\"authors\":\"Ching-Wen Ma, C. Teng\",\"doi\":\"10.1109/AFSS.1996.583596\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The single-source near-field direction finding problem can be solved by a fuzzy neural network (FNN). The FNN approach can be applied to arrays with arbitrary configurations. It can also be implemented for real-time tracking applications. The approach outperforms the far-field approximation (FFA) approach when the array is uniformly-spaced and linear, especially when the angle between the array normal direction and the source direction is large and the distance from array center to the source is short.\",\"PeriodicalId\":197019,\"journal\":{\"name\":\"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium\",\"volume\":\"55 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-12-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AFSS.1996.583596\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AFSS.1996.583596","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Near-field direction finding with a fuzzy neural network
The single-source near-field direction finding problem can be solved by a fuzzy neural network (FNN). The FNN approach can be applied to arrays with arbitrary configurations. It can also be implemented for real-time tracking applications. The approach outperforms the far-field approximation (FFA) approach when the array is uniformly-spaced and linear, especially when the angle between the array normal direction and the source direction is large and the distance from array center to the source is short.