国产原子钟的噪声及守时性能研究  

Study on noise and time keeping performance of homemade atomic clocks

作　　者：宋会杰[1] 董绍武[1,2] 王翔 王燕平[1] 张继海[1] 屈俐俐[1] 赵书红[1] 张首刚[1,2] SONG Hui jie;DONG Shao wu;WANG Xiang;WANG Yan ping;ZHANG Ji hai;QU Li li;ZHAO Shu hong;ZHANG Shou gang(National Time Service Center,Chinese Academy of Sciences,Xi’an 710600,China;School of Astronomy and Space Science,University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]中国科学院国家授时中心,西安710600 [2]中国科学院大学天文与空间科学学院,北京100049

出　　处：《时间频率学报》2022年第4期270-278,共9页Journal of Time and Frequency

基　　金：中国科学院“西部之光”人才培养计划“西部青年学者”资助项目(XAB2021YN22);北京无线电计量测试研究所开放基金资助项目(JLJK2021001A002)

摘　　要：我国时间工作在取得长足进步的同时,也面临着解决关键核心技术问题,加速守时系统关键设备的国产化进程,开展基于国产原子钟的时间基准保持关键技术研究,解决我国标准时间自主产生是当前面临的迫切问题。时间基准保持关键技术研究的基础是国产原子钟噪声及守时性能的分析。文中通过对国产原子钟测量数据进行小波多尺度分解,得出不同分解尺度下的噪声强度。分别基于经典加权平均算法和Kalman滤波算法计算国产钟所产生的纸面时间尺度,并比较2个时间尺度的准确度、稳定度和实时性。得出Kalman滤波时间尺度的准确度优于经典加权平均算法,5天以上的稳定度优于经典加权平均算法时间尺度的稳定度,并且Kalman滤波算法实时性强。While China’s time keeping work has made great progress,it is also faced with solving key core technical issues,to speeding up the localization process of key equipment of the time keeping system,it is an urgent problem to study the key technology of time keeping based on homemade atomic clocks and solve the problem of our country’s standard time.The research of key technology of time keeping is based on the study of noise and performance of homemade atomic clocks.In this paper,the measurement data of atomic clocks are decomposed by wavelet multi scale,and the noise intensity under different decomposition scale is obtained.Based on the classical weighted average algorithm and Kalman filter algorithm,the time scales of homemade clocks are calculated,and the accuracies,stabilities and real time performance of the time scales are compared.The results show that the time scale accuracy of Kalman filtering is better than that of classical weighted average algorithm,and the stability of Kalman filtering is better than that of classical weighted average algorithm after 5 days,and the real time performance of Kalman filtering algorithm is strong.

关 键 词：原子钟噪声 时间尺度 小波变换 KALMAN滤波 

分 类 号：P127.1[天文地球—天体测量]