@article{Cao2025, 
author = {Zhuojian Cao and Jiang Liu and Wei Jiang and Baigen Cai},
title = {INS-aided GNSS jamming protection in support of resilient train positioning},
year = {2025},
journal = {High-speed Railway},
volume = {3},
number = {3},
pages = {185-193},
keywords = {GNSS jamming, Deeply-coupled integration, GNSS/INS},
url = {https://www.sciopen.com/article/10.1016/j.hspr.2025.05.004},
doi = {10.1016/j.hspr.2025.05.004},
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.}
}