电讯技术2025，Vol.65Issue(6)：939-946,8.DOI:10.20079/j.issn.1001-893x.240913002
拒止环境下分布式平台高精度相对时差预报方法
High Precision Relative Clock Error Prediction in Denial Environment
摘要
Abstract
Time-frequency synchronization is an important support technology of distributed system.When the platform enters the specific hostile environment,the navigation satellites and communication signals are easily jammed or blocked,and cannot continue to maintain high-precision time-frequency synchronization.In order to solve above problem,the authors firstly analyze the characteristics of Kalman filter(KF),gray model(GM)and autoregressive integrated moving average model(ARIMA),and propose a combined forecasting model based on weighted method.Then prediction accuracy and characteristic rules of each model are analyzed under different predict time length conditions,by building an experimental verification environment combined with the relative clock bias data based on differential Beidou and the micro-rubidium clock.Test results show that the prediction accuracy of KF or ARIMA model is better than that of GM model and the error of the predicted relative clock bias is less than 0.5 ns,and the error of the predicted relative frequency bias is less than 2×10-11 when the satellite navigation is unavailable for 1 500 s or less.The stationarity of the prediction error of KF and ARIMA model is better than the relative clock bias data when the available measurement data duration is greater than 300 s.The prediction accuracy and stationarity of the KF+ARIMA+GM combined model are all better than that of the single model.关键词
分布式平台/区域拒止/时频同步/模型预报Key words
distributed platform/area denial/time-frequency synchronization/prediction model分类
电子信息工程引用本文复制引用
班亚龙,康荣雷,李沛洲,常军..拒止环境下分布式平台高精度相对时差预报方法[J].电讯技术,2025,65(6):939-946,8.
