INS-aided GNSS jamming protection in support of resilient train positioning

Railway safety and efficiency increasingly rely on precise train positioning. The integration of 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 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 RF jamming threats.

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Publication Details

Journal
High-speed Railway
Published
2025-05-26
DOI
https://doi.org/10.1016/j.hspr.2025.05.004
Primary Topic
Indoor and Outdoor Localization Technologies
Type
article
Field-Weighted Citation Impact
0.00

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article

INS-aided GNSS jamming protection in support of resilient train positioning

Zhuojian Cao, Wei Jiang, Baigen Cai, Jiang Liu
High-speed Railway
Indoor and Outdoor Localization Technologies
article

INS-aided GNSS jamming protection in support of resilient train positioning

Zhuojian Cao, Wei Jiang, Baigen Cai, Jiang Liu
article en

Abstract

Railway safety and efficiency increasingly rely on precise train positioning. The integration of 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 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 RF jamming threats.

High-speed RailwayVol. 3(3)
Beijing Jiaotong University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Beijing Municipality
Climate action
Openalex Percentile: Top 90%
Indoor and Outdoor Localization Technologies
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