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Researchers Detect Atomic Clock Frequency Anomaly by Adaptive Kalman Filter Algorithm

May 14, 2018     Email"> PrintText Size

The abnormal frequencies of an atomic clock mainly include frequency jump and frequency drift jump. Atomic clock frequency anomaly detection is a key technique in time-keeping. 

Obvious frequency anomalies can be easily detected by traditional measurement like allan variance and power spectral density, but it is difficult to detect tiny anomalies through these methods.  

Recently, researchers from the Key Laboratory of Time-frequency Standard of National Time Service Center (NTSC) of the Chinese Academy of Sciences made progress in time-keeping theory and method. Their findings were published in Metrologia, a leading international journal in the field of time frequency. 

The study is significant for keeping China’s time reference. It introduces how to detect an atomic clock frequency anomaly by using an adaptive Kalman filter algorithm, improving on the traditional mathematic model algorithm.  

Based on the analysis of stimulated clock data and the atomic clock data from the UTC (NTSC) time reference system, researchers found  that compared with the classical Kalman filter algorithm, adaptive Kalman filter algorithm had higher probability of detecting frequency anomalies and it took shorter time in detection, making a very promising method in maintaining time reference.  

In recent years, NTSC has been contributing to improving the performance of the national standard time, developing methods to evaluate atomic clock performance, and carrying out innovative researches on integrated multi-links GNSS time transfer methods as well as applications of reference clocks to time-keeping systems.


(Editor: LI Yuan)



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