Modeling and performance analysis of GNSS-based train positioning system with colored petri nets

Abstract

Global Navigation Satellite System (GNSS)-based continuous and accurate train positioning is one of the key technologies for advanced train operations such as train virtual coupling. However, GNSS-based train positioning faces significant challenges in real-world scenarios due to environmental complexities and signal interferences. Considering this issue, this paper presents an approach for modeling and performance analysis of GNSS-based train positioning systems using Colored Petri Nets (CPNs). By systematically modeling the GNSS signal reception and processing process, the performance of the positioning system under various environment scenarios is evaluated. The system model integrates three types of interference signals (i.e., Amplitude Modulation (AM) signals, Frequency Modulation (FM) signals, and pulse signals) while incorporating environmental factors such as terrain obstructions and tunnel shielding. Additionally, the Extended Kalman Filter (EKF) algorithm is employed to process GNSS observation data, providing accurate train position estimations. The simulation results demonstrate that signal interferences and complex environmental conditions significantly affect the GNSS-based positioning accuracy. This study offers a comprehensive framework for evaluating the performance of GNSS-based train positioning systems in different scenarios, highlighting critical factors that influence positioning accuracy and stability.

Keywords

GNSS-based train positioning / Positioning performance / Environment scenario / GNSS signal interference / Colored petri Nets

CRediT authorship contribution statement

Siqi Wang: Writing – review & editing, Software, Data curation. Shuting Chen: Writing – original draft, Validation, Methodology, Formal analysis. Daohua Wu: Writing – review & editing, Supervision, Methodology, Conceptualization. Jiang Liu: Writing – review & editing, Funding acquisition, Conceptualization.

Declaration of Competing Interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement

This work was supported by the National Key Research and Development Program of China (2023YFB3907300), the Fundamental Research Funds for the Central Universities (2024JBMC002), and the National Natural Science Foundation of China (T2222015, U2268206 ).

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