{"title":"基于混合神经网络模型的辐射源二维方位精确估计","authors":"M. Agatonovic, Z. Stanković","doi":"10.1109/TELSKS.2013.6704401","DOIUrl":null,"url":null,"abstract":"Given that simulation models may often suffer from reduced accuracy when applied to real environmental conditions, in this paper we propose a hybrid model for two-dimensional direction of arrival (2D DOA) estimation of a radiating source. The model is based on artificial neural networks (ANNs), and its development is conducted in two phases. Initially, an ANN is trained to predict angular positions of a simulated radiating source in a certain range of azimuth and elevation angles. The second phase includes development of a corrective empirical ANN aimed to improve the accuracy of the simulation-based network. Finally, the hybrid ANN model is able to account for real environmental conditions and physical aspects of the receiving antenna array. The performance of the model is verified by measurements for several positions of the transmitting antenna.","PeriodicalId":144044,"journal":{"name":"2013 11th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services (TELSIKS)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Hybrid ANN model for accurate 2D DOA estimation of a radiating source\",\"authors\":\"M. Agatonovic, Z. Stanković\",\"doi\":\"10.1109/TELSKS.2013.6704401\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Given that simulation models may often suffer from reduced accuracy when applied to real environmental conditions, in this paper we propose a hybrid model for two-dimensional direction of arrival (2D DOA) estimation of a radiating source. The model is based on artificial neural networks (ANNs), and its development is conducted in two phases. Initially, an ANN is trained to predict angular positions of a simulated radiating source in a certain range of azimuth and elevation angles. The second phase includes development of a corrective empirical ANN aimed to improve the accuracy of the simulation-based network. Finally, the hybrid ANN model is able to account for real environmental conditions and physical aspects of the receiving antenna array. The performance of the model is verified by measurements for several positions of the transmitting antenna.\",\"PeriodicalId\":144044,\"journal\":{\"name\":\"2013 11th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services (TELSIKS)\",\"volume\":\"84 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 11th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services (TELSIKS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TELSKS.2013.6704401\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 11th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services (TELSIKS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TELSKS.2013.6704401","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Hybrid ANN model for accurate 2D DOA estimation of a radiating source
Given that simulation models may often suffer from reduced accuracy when applied to real environmental conditions, in this paper we propose a hybrid model for two-dimensional direction of arrival (2D DOA) estimation of a radiating source. The model is based on artificial neural networks (ANNs), and its development is conducted in two phases. Initially, an ANN is trained to predict angular positions of a simulated radiating source in a certain range of azimuth and elevation angles. The second phase includes development of a corrective empirical ANN aimed to improve the accuracy of the simulation-based network. Finally, the hybrid ANN model is able to account for real environmental conditions and physical aspects of the receiving antenna array. The performance of the model is verified by measurements for several positions of the transmitting antenna.