{"title":"INS-aided GNSS jamming protection in support of resilient train positioning","authors":"Zhuojian Cao , Jiang Liu , Wei Jiang , Baigen Cai","doi":"10.1016/j.hspr.2025.05.004","DOIUrl":null,"url":null,"abstract":"<div><div>Railway safety and efficiency increasingly rely on precise train positioning. The integration of the Global Navigation Satellite System (GNSS) into railway control systems aims to reduce dependence on track-side infrastructure. While GNSS has significantly improved train localization, challenges such as the susceptibility to jamming remain. To address this, this paper introduces an Inertial Navigation System (INS)-aided train positioning system based on deep integration, exploring its performance through semi-physical experiments and simulations. Experimental results demonstrate that the proposed solution is able to reduce the positioning error by 63.47 %, and the velocity error by 58.47 % under jamming conditions. The study highlights the potential of deep integration for improving the resilience of GNSS-based train control systems, especially in the face of Radio Frequency (RF) jamming threats.</div></div>","PeriodicalId":100607,"journal":{"name":"High-speed Railway","volume":"3 3","pages":"Pages 185-193"},"PeriodicalIF":0.0000,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"High-speed Railway","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2949867825000261","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
Railway safety and efficiency increasingly rely on precise train positioning. The integration of the Global Navigation Satellite System (GNSS) into railway control systems aims to reduce dependence on track-side infrastructure. While GNSS has significantly improved train localization, challenges such as the susceptibility to jamming remain. To address this, this paper introduces an Inertial Navigation System (INS)-aided train positioning system based on deep integration, exploring its performance through semi-physical experiments and simulations. Experimental results demonstrate that the proposed solution is able to reduce the positioning error by 63.47 %, and the velocity error by 58.47 % under jamming conditions. The study highlights the potential of deep integration for improving the resilience of GNSS-based train control systems, especially in the face of Radio Frequency (RF) jamming threats.