Dan Zhao, Min Huang, Peng Li, Luan Wang, Renhong Xie, Yibin Rui
{"title":"An Effective Method of Collided Signals Separation for Satellite-based Automatic Identification System","authors":"Dan Zhao, Min Huang, Peng Li, Luan Wang, Renhong Xie, Yibin Rui","doi":"10.1109/IMWS-AMP49156.2020.9199722","DOIUrl":null,"url":null,"abstract":"In this paper, an effective method which is developed specially for separating the collided wireless RF signals of satellite-based Automatic Identification System (AIS) is presented. The proposed approach adopts an optimization algorithm, which improves the artificial bee colony (ABC) algorithm by combining the advantages of limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS). The separation mathematical model of the collided signals is addressed and the steps of algorithm are given. Simulation results show that the proposed method yields superior performance in terms of convergence speed and solution accuracy.","PeriodicalId":163276,"journal":{"name":"2020 IEEE MTT-S International Microwave Workshop Series on Advanced Materials and Processes for RF and THz Applications (IMWS-AMP)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE MTT-S International Microwave Workshop Series on Advanced Materials and Processes for RF and THz Applications (IMWS-AMP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMWS-AMP49156.2020.9199722","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
In this paper, an effective method which is developed specially for separating the collided wireless RF signals of satellite-based Automatic Identification System (AIS) is presented. The proposed approach adopts an optimization algorithm, which improves the artificial bee colony (ABC) algorithm by combining the advantages of limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS). The separation mathematical model of the collided signals is addressed and the steps of algorithm are given. Simulation results show that the proposed method yields superior performance in terms of convergence speed and solution accuracy.