Time-Frequency Signal Integrity Monitoring Algorithm Based on Temperature Compensation Frequency Bias Combination Model

被引:1
|
作者
Guo, Yu [1 ,2 ]
Li, Zongnan [1 ,2 ]
Gong, Hang [1 ,2 ]
Peng, Jing [1 ,2 ]
Ou, Gang [1 ,2 ]
机构
[1] Natl Univ Def Technol NUDT, Coll Elect Sci & Technol, Changsha 410073, Peoples R China
[2] Key Lab Satellite Nav Technol, Changsha 410073, Peoples R China
基金
国家重点研发计划;
关键词
time-frequency signal; integrity monitoring; time-frequency system; feature extraction; temperature compensation; GNSS; SCHEME;
D O I
10.3390/rs16081453
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
To ensure the long-term stable and uninterrupted service of satellite navigation systems, the robustness and reliability of time-frequency systems are crucial. Integrity monitoring is an effective method to enhance the robustness and reliability of time-frequency systems. Time-frequency signals are fundamental for integrity monitoring, with their time differences and frequency biases serving as essential indicators. These indicators are influenced by the inherent characteristics of the time-frequency signals, as well as the links and equipment they traverse. Meanwhile, existing research primarily focuses on only monitoring the integrity of the time-frequency signals' output by the atomic clock group, neglecting the integrity monitoring of the time-frequency signals generated and distributed by the time-frequency signal generation and distribution subsystem. This paper introduces a time-frequency signal integrity monitoring algorithm based on the temperature compensation frequency bias combination model. By analyzing the characteristics of time difference measurements, constructing the temperature compensation frequency bias combination model, and extracting and monitoring noise and frequency bias features from the time difference measurements, the algorithm achieves comprehensive time-frequency signal integrity monitoring. Experimental results demonstrate that the algorithm can effectively detect, identify, and alert users to time-frequency signal faults. Additionally, the model and the integrity monitoring parameters developed in this paper exhibit high adaptability, making them directly applicable to the integrity monitoring of time-frequency signals across various links. Compared with traditional monitoring algorithms, the algorithm proposed in this paper greatly improves the effectiveness, adaptability, and real-time performance of time-frequency signal integrity monitoring.
引用
收藏
页数:18
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