Resilient GNSS/INS-Based Railway Train Localization Using Odometer/Trackmap-Enabled Jamming Discrimination
Technological advances in the Global Navigation Satellite System (GNSS) industry have brought significant advantages in enhancing the cost-efficiency of railway applications. However, GNSS vulnerability to external jamming necessitates enhanced protection ability of the GNSS-based train localization system. This paper proposes a resilient train localization solution under the tightly-coupled integration scheme. This solution maximizes the utilization of multi-source information from train-borne sensors, including INS, odometer, and the trackmap database. Based on the existing localization scheme, it achieves a compatible way to address different jamming-intrusion situations without altering the GNSS receiver structure, addressing both the GNSS failure and degradation caused by jamming. Using an odometer/trackmap-enabled equivalent measurement logic, the continuity of localization can be guaranteed against GNSS failure under strong GNSS jamming. A robust filtering algorithm enabled by a jamming discrimination mechanism is proposed for GNSS/INS integration to mitigate the negative effect from degraded GNSS measurements, reducing the hazards by jamming with an intermediate power level. Based on the field data and a jamming test platform, results under two typical jamming scenarios are evaluated to demonstrate the necessity and superiority of the proposed solution. It also emphasizes the importance of the full-life-cycle resilience of GNSS-based train localization under the railway operation environment.
Authors
- Zhuojian Cao
- Wei Jiang (ORCID: https://orcid.org/0000-0001-6381-4915)
- Baigen Cai (ORCID: https://orcid.org/0000-0002-6440-005X)
- Jian Wang (ORCID: https://orcid.org/0000-0003-1748-6409)
- Jiang Liu (ORCID: https://orcid.org/0000-0002-2836-7651)
Institutions
- Beijing Jiaotong University (CN)
Publication Details
- Journal
- IEEE Transactions on Intelligent Transportation Systems
- Published
- 2024-10-09
- DOI
- https://doi.org/10.1109/tits.2024.3460689
- Citations
- 3
- Primary Topic
- Vehicle License Plate Recognition
- Type
- article
- Field-Weighted Citation Impact
- 0.96
Funders
- National Natural Science Foundation of China
- Fundamental Research Funds for the Central Universities