GNSS 수신기 간 시각 동기 유지를 위한 시계 오차 모델링 기법 비교
Comparison of Clock Drift Modeling Methods for Maintaining Time Synchronization Between GNSS Receivers
0
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
Precise time synchronization among distributed infrastructure is essential for enhancing the performance of systems such as wireless sensor networks, cellular base stations, and terrestrial navigation systems. Global Navigation Satellite System (GNSS) time transfer is a widely used method for synchronizing remote receivers; however, due to communication or operational constraints, it is often performed only intermittently at periodic intervals. During these intervals, clock offsets between receivers may accumulate due to clock drift and can lead to degraded time synchronization accuracy. To address this issue, this study evaluates and compares three clock drift modeling methods—moving average, polynomial fitting, and Kalman filtering—for predicting and compensating clock offsets between GNSS receivers in the absence of continuous GNSS time transfer. Both 2-state and 3-state Kalman filter models are considered to examine how the number of state variables affects prediction performance. Experiments were conducted using real data collected from two GNSS receivers: one disciplined by an external rubidium atomic clock and the other steered to GPST. The results show that when the GNSS time transfer interval is less than 20 hours, the 2-state Kalman filter achieves the best performance, whereas the 3-state Kalman filter performs better for longer intervals. These findings provide practical guidelines for selecting appropriate clock drift compensation strategies and GNSS synchronization intervals based on timing accuracy requirements and system constraints.
Abstract
Precise time synchronization among distributed infrastructure is essential for enhancing the performance of systems such as wireless sensor networks, cellular base stations, and terrestrial navigation systems. Global Navigation Satellite System (GNSS) time transfer is a widely used method for synchronizing remote receivers; however, due to communication or operational constraints, it is often performed only intermittently at periodic intervals. During these intervals, clock offsets between receivers may accumulate due to clock drift and can lead to degraded time synchronization accuracy. To address this issue, this study evaluates and compares three clock drift modeling methods—moving average, polynomial fitting, and Kalman filtering—for predicting and compensating clock offsets between GNSS receivers in the absence of continuous GNSS time transfer. Both 2-state and 3-state Kalman filter models are considered to examine how the number of state variables affects prediction performance. Experiments were conducted using real data collected from two GNSS receivers: one disciplined by an external rubidium atomic clock and the other steered to GPST. The results show that when the GNSS time transfer interval is less than 20 hours, the 2-state Kalman filter achieves the best performance, whereas the 3-state Kalman filter performs better for longer intervals. These findings provide practical guidelines for selecting appropriate clock drift compensation strategies and GNSS synchronization intervals based on timing accuracy requirements and system constraints.