{"title":"基于传播器方法和特征空间波束形成器的鲁棒自适应波束形成","authors":"Yu Pengcheng, Yang Peng, Y. Fei","doi":"10.1109/CSQRWC.2012.6294999","DOIUrl":null,"url":null,"abstract":"A novel algorithm based on propagator method (PM) and Eigenspace Beamformer (ESB) for robust adaptive beamforming is presented. It has robust characteristics under the conditions of finite samples, desired signal point error and high SNR environment. By using PM, the signal subspace can be derived by propagator matrix, which does not need the complicated eigenvalue decomposition (EVD) or singular-value decomposition (SVD). The efficiency of this method is verified by numerical simulations.","PeriodicalId":250360,"journal":{"name":"CSQRWC 2012","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Robust adaptive beamforming based on propagator method and Eigenspace Beamformer\",\"authors\":\"Yu Pengcheng, Yang Peng, Y. Fei\",\"doi\":\"10.1109/CSQRWC.2012.6294999\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A novel algorithm based on propagator method (PM) and Eigenspace Beamformer (ESB) for robust adaptive beamforming is presented. It has robust characteristics under the conditions of finite samples, desired signal point error and high SNR environment. By using PM, the signal subspace can be derived by propagator matrix, which does not need the complicated eigenvalue decomposition (EVD) or singular-value decomposition (SVD). The efficiency of this method is verified by numerical simulations.\",\"PeriodicalId\":250360,\"journal\":{\"name\":\"CSQRWC 2012\",\"volume\":\"53 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-07-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"CSQRWC 2012\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSQRWC.2012.6294999\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"CSQRWC 2012","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSQRWC.2012.6294999","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Robust adaptive beamforming based on propagator method and Eigenspace Beamformer
A novel algorithm based on propagator method (PM) and Eigenspace Beamformer (ESB) for robust adaptive beamforming is presented. It has robust characteristics under the conditions of finite samples, desired signal point error and high SNR environment. By using PM, the signal subspace can be derived by propagator matrix, which does not need the complicated eigenvalue decomposition (EVD) or singular-value decomposition (SVD). The efficiency of this method is verified by numerical simulations.