{"title":"An optimal method for narrowband interference mitigation in the GPS","authors":"M. Nouri, S. Abazari Aghdam, V. Tabataba Vakili","doi":"10.1109/ICMSAO.2011.5775480","DOIUrl":null,"url":null,"abstract":"In this paper an optimal method for reducing interference to narrowband GPS interference is presented. In this method, Fast Transversal RLS algorithm is used. An Adaptive Temporal Filter (ATF) based on a Transversal form that pre-filters the interference before correlation is studied. This algorithm is designed to provide similar performance to the standard RLS algorithm while reducing the computation order. The adaptive algorithm used to adjust the filter coefficients is the FT-RLS algorithm. This algorithm has faster convergence and is independent of the gradient step size when compared to LMS, NLMS, RLS, QR-decomposition-based RLS and Sliding window-RLS algorithms. We present initial results on the performance of the described interference cancellation methods.","PeriodicalId":6383,"journal":{"name":"2011 Fourth International Conference on Modeling, Simulation and Applied Optimization","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Fourth International Conference on Modeling, Simulation and Applied Optimization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMSAO.2011.5775480","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In this paper an optimal method for reducing interference to narrowband GPS interference is presented. In this method, Fast Transversal RLS algorithm is used. An Adaptive Temporal Filter (ATF) based on a Transversal form that pre-filters the interference before correlation is studied. This algorithm is designed to provide similar performance to the standard RLS algorithm while reducing the computation order. The adaptive algorithm used to adjust the filter coefficients is the FT-RLS algorithm. This algorithm has faster convergence and is independent of the gradient step size when compared to LMS, NLMS, RLS, QR-decomposition-based RLS and Sliding window-RLS algorithms. We present initial results on the performance of the described interference cancellation methods.