Model-Driven Clock Synchronization Algorithms for Random Loss of GNSS Time Signals in V2X Communications
Onboard Vehicle-to-Everything (V2X) communication technology is being widely implemented in domains such as intelligent driving, vehicle–road cooperation, and smart transportation. Nevertheless, time synchronization in V2X systems suffers from instability due to the random loss of Global Navigation...
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MDPI AG
2025-06-01
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| author | Wei Hu Jiajie Zhang Ximing Cheng |
| author_facet | Wei Hu Jiajie Zhang Ximing Cheng |
| author_sort | Wei Hu |
| collection | DOAJ |
| description | Onboard Vehicle-to-Everything (V2X) communication technology is being widely implemented in domains such as intelligent driving, vehicle–road cooperation, and smart transportation. Nevertheless, time synchronization in V2X systems suffers from instability due to the random loss of Global Navigation Satellite System (GNSS) Pulse-Per-Second (PPS) signals. To address this challenge, a model-driven local clock correction approach is proposed. Leveraging probability theory and mathematical statistics, models for the randomly lost GNSS PPS signals are developed. High-order polynomials are used to model local clocks. An optimized Kalman-filter-based time compensation algorithm is then devised to compensate for time errors during PPS signal loss. A software-based task-scheduling solution for precision-time synchronization is developed. An experimental testbed was then built to measure both terminal clocks and PPS signals. The proposed algorithm was integrated into the V2X terminals. Results show that the full-value PPS signals follow an exponential distribution. The onboard clock correction algorithm operates stably across three V2X terminals and accurately predicts clock variations. Furthermore, the virtual clocks achieve an average absolute error of 1.1 μs and a standard deviation of 16 μs, meeting the time synchronization requirements for V2X communication in intelligent connected vehicles. |
| format | Article |
| id | doaj-art-3e148fb9d870403c8d33df1541aa15cd |
| institution | DOAJ |
| issn | 2227-7080 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
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| series | Technologies |
| spelling | doaj-art-3e148fb9d870403c8d33df1541aa15cd2025-08-20T02:47:21ZengMDPI AGTechnologies2227-70802025-06-0113727310.3390/technologies13070273Model-Driven Clock Synchronization Algorithms for Random Loss of GNSS Time Signals in V2X CommunicationsWei Hu0Jiajie Zhang1Ximing Cheng2School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, ChinaOnboard Vehicle-to-Everything (V2X) communication technology is being widely implemented in domains such as intelligent driving, vehicle–road cooperation, and smart transportation. Nevertheless, time synchronization in V2X systems suffers from instability due to the random loss of Global Navigation Satellite System (GNSS) Pulse-Per-Second (PPS) signals. To address this challenge, a model-driven local clock correction approach is proposed. Leveraging probability theory and mathematical statistics, models for the randomly lost GNSS PPS signals are developed. High-order polynomials are used to model local clocks. An optimized Kalman-filter-based time compensation algorithm is then devised to compensate for time errors during PPS signal loss. A software-based task-scheduling solution for precision-time synchronization is developed. An experimental testbed was then built to measure both terminal clocks and PPS signals. The proposed algorithm was integrated into the V2X terminals. Results show that the full-value PPS signals follow an exponential distribution. The onboard clock correction algorithm operates stably across three V2X terminals and accurately predicts clock variations. Furthermore, the virtual clocks achieve an average absolute error of 1.1 μs and a standard deviation of 16 μs, meeting the time synchronization requirements for V2X communication in intelligent connected vehicles.https://www.mdpi.com/2227-7080/13/7/273V2XGNSStime synchronizationPPS sequence modelKalman filter |
| spellingShingle | Wei Hu Jiajie Zhang Ximing Cheng Model-Driven Clock Synchronization Algorithms for Random Loss of GNSS Time Signals in V2X Communications Technologies V2X GNSS time synchronization PPS sequence model Kalman filter |
| title | Model-Driven Clock Synchronization Algorithms for Random Loss of GNSS Time Signals in V2X Communications |
| title_full | Model-Driven Clock Synchronization Algorithms for Random Loss of GNSS Time Signals in V2X Communications |
| title_fullStr | Model-Driven Clock Synchronization Algorithms for Random Loss of GNSS Time Signals in V2X Communications |
| title_full_unstemmed | Model-Driven Clock Synchronization Algorithms for Random Loss of GNSS Time Signals in V2X Communications |
| title_short | Model-Driven Clock Synchronization Algorithms for Random Loss of GNSS Time Signals in V2X Communications |
| title_sort | model driven clock synchronization algorithms for random loss of gnss time signals in v2x communications |
| topic | V2X GNSS time synchronization PPS sequence model Kalman filter |
| url | https://www.mdpi.com/2227-7080/13/7/273 |
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