{"title":"Adaptive filtration of random signals in active antenna array with nonlinear transmit/receive modules","authors":"Y. Parshin, S. Kolesnikov","doi":"10.1109/ICUMT.2016.7765400","DOIUrl":null,"url":null,"abstract":"The methods of filtration accuracy enhancement of random signal in active antenna array with prior uncertainty of nonlinearity factor in receiving channels are investigated. Based on Markov model of random signal and 3-th order nonlinearity model the synthesis of quasi linear filtration algorithm is implemented. The development of algorithm of nonlinearity factor adaptive adjustment is carried out by means of innovation process method. The filtration error variance sensitivity vs nonlinearity factor mismatch is calculated for efficiency estimation of obtained algorithm. The convergence of adaptive adjustment of nonlinearity factor is validated through correspondence of averaged discriminator characteristic curve with character of mismatch of nonlinearity factor.","PeriodicalId":174688,"journal":{"name":"2016 8th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 8th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICUMT.2016.7765400","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The methods of filtration accuracy enhancement of random signal in active antenna array with prior uncertainty of nonlinearity factor in receiving channels are investigated. Based on Markov model of random signal and 3-th order nonlinearity model the synthesis of quasi linear filtration algorithm is implemented. The development of algorithm of nonlinearity factor adaptive adjustment is carried out by means of innovation process method. The filtration error variance sensitivity vs nonlinearity factor mismatch is calculated for efficiency estimation of obtained algorithm. The convergence of adaptive adjustment of nonlinearity factor is validated through correspondence of averaged discriminator characteristic curve with character of mismatch of nonlinearity factor.