The variations in the Earth's rotation are important to space dynamic theory and natural disasters because they affect the length-of-day(LOD) and consequently human lives. We use maximum entropy method(MEM), Lomb ...The variations in the Earth's rotation are important to space dynamic theory and natural disasters because they affect the length-of-day(LOD) and consequently human lives. We use maximum entropy method(MEM), Lomb method(LOMB), and phase dispersion minimization(PDM) to determine the natural periods of equally spaced LOD time series. We transform the observational monthly LOD time series(LODM) to unequally sampled series(LODMD) by removing every fourth, third, and half of the total samples. We also apply spline interpolation to LODMD to yield equally spaced time series(LODMDN). The results suggest that regardless of the time series, the MEM frequency is 0.1660 month^(-1) and 0.0840 month^(-1), whereas LOMB and PDM yield 0.166 month^(-1) and 0.083 month^(-1), respectively. Furthermore, missing data that are less than half of the total data or spline interpolation do not affect the analysis. For the amplitude, neither missing data nor spline interpolation affect the analysis.展开更多
Period estimation of X-ray pulsars plays an important role in X-ray pulsar based navigation （XPNAV）. The fast Lomb periodogram is suitable for period estimation of X-ray pulsars, but its performance in terms of freq...Period estimation of X-ray pulsars plays an important role in X-ray pulsar based navigation （XPNAV）. The fast Lomb periodogram is suitable for period estimation of X-ray pulsars, but its performance in terms of frequency resolution is limited by data length and observation time. Longer observation time or oversampling can be employed to improve frequency analysis results, but with greatly increased computational complexity and large amounts of sampling data. This greatly restricts real-time autonomous navigation based on X-ray pulsars. To resolve this issue, a new method based on frequency subdivision and the continuous Lomb periodogram （CLP） is proposed to improve precision of period estimation using short-time observation data. In the proposed method, an initial frequency is first calculated using fast Lomb periodogram. Then frequency subdivision is per- formed near the initial frequency to obtain frequencies with higher precision. Finally, a refined period is achieved by calculating the CLP in the obtained frequencies. Real data experiments show that when observation time is shorter than 135 s, the proposed method improves period estimation precision by 1-3 orders of magnitude compared with the fast Lomb periodogram and fast Fourier transform （FFT） methods, with only a slight increase in computational complexity. Furthermore, the proposed method performs better than efsearch （a period estimation method of HEAsoft） with lower computational complexity. The proposed method is suitable for estimating periods of X-ray pulsars and obtaining the rotation period of variable stars and other celestial bodies.展开更多
利用GNSS-MR(Global Navigation Satellite System Multipath Reflectometry)技术反演积雪深度是近年来一种新兴的卫星遥感技术。目前大多数研究仅使用GPS(Global Position System)数据限制了该技术的发展,为了扩展GNSS-MR算法的应用,...利用GNSS-MR(Global Navigation Satellite System Multipath Reflectometry)技术反演积雪深度是近年来一种新兴的卫星遥感技术。目前大多数研究仅使用GPS(Global Position System)数据限制了该技术的发展,为了扩展GNSS-MR算法的应用,介绍了基于GNSS-MR算法的雪深反演模型。首先,通过多项式拟合分解GLONASS观测数据获取高精度的信噪比残差序列;然后,利用Lomb-Scargle谱分析法对其进行频谱分析可解算雪深值。选取IGS中心的YEL2站2015年11月到2016年6月共243天的GLONASS卫星L1波段反射信号的SNR数据进行实例分析,并以美国国家气象数据中心提供的加拿大Y-H (Yellowknife Henderson)气象站的实测雪深数据为真值,将反演雪深与实测雪深进行对比验证。所得实验结果如下:(1)与GPS卫星的反演值相比,基于GLONASS-MR(GLONASS Multipath Reflectometry)技术反演积雪深度的精度同样能达到厘米级,RMSE仅3.3 cm,反演值与实测值的空间分布趋势一致且相关性较强,其相关系数R2高达0.969;(2)不同的积雪深度对信噪比的振幅频率与垂直反射距离具有直接影响;(3)对同一卫星而言,信噪比的频谱振幅强度峰值与其对应的反演值存在线性相关;(4)在相同条件下,采用多颗GLONASS卫星数据比单颗GLONASS卫星数据反演雪深的效果明显更优。基于反演的高时间分辨率产品,分析该地区雪深日变化的情况,实验结果表明基于陆基CORS站的GLONASS-MR技术在用于实时、连续的雪深变化监测方面具有良好的潜力和可行性。展开更多
Using the Lomb-Scargle periodogram we analyzed two sunspot series: the one over the past 11000 years at the 10-year interval based upon the survey data of 14C concentration in tree-rings, recon- structed by Solanki et...Using the Lomb-Scargle periodogram we analyzed two sunspot series: the one over the past 11000 years at the 10-year interval based upon the survey data of 14C concentration in tree-rings, recon- structed by Solanki et al.; and the sunspot number over the past 7000 years, derived from geomagnetic variations by Usoskin et al. We found the periods and quasi-periods in solar activity, such as about 225, 352, 441, 522 and 561 a, and near 1000 and 2000 a. An approach of wavelet transform was applied to check the two sunspot time series, with emphasis on investigating time-varying characteristics in the long-term fluctuations of solar activity. The results show that the lengths and amplitudes of the periods have changed with time, and large variations have taken place during some periods.展开更多
基金supported by the National Natural Science Foundation of China(No.11203004)the Fundamental Research Funds for the Central Universities
文摘The variations in the Earth's rotation are important to space dynamic theory and natural disasters because they affect the length-of-day(LOD) and consequently human lives. We use maximum entropy method(MEM), Lomb method(LOMB), and phase dispersion minimization(PDM) to determine the natural periods of equally spaced LOD time series. We transform the observational monthly LOD time series(LODM) to unequally sampled series(LODMD) by removing every fourth, third, and half of the total samples. We also apply spline interpolation to LODMD to yield equally spaced time series(LODMDN). The results suggest that regardless of the time series, the MEM frequency is 0.1660 month^(-1) and 0.0840 month^(-1), whereas LOMB and PDM yield 0.166 month^(-1) and 0.083 month^(-1), respectively. Furthermore, missing data that are less than half of the total data or spline interpolation do not affect the analysis. For the amplitude, neither missing data nor spline interpolation affect the analysis.
基金Project supported by the National Basic Research Program(973)of China(No.2014CB340205)the National Natural Science Foundation of China(Nos.61301173 and 61473228)the Aerospaced TT&C Innovation Program of 704 Research Institute of China(No.201405B)
文摘Period estimation of X-ray pulsars plays an important role in X-ray pulsar based navigation （XPNAV）. The fast Lomb periodogram is suitable for period estimation of X-ray pulsars, but its performance in terms of frequency resolution is limited by data length and observation time. Longer observation time or oversampling can be employed to improve frequency analysis results, but with greatly increased computational complexity and large amounts of sampling data. This greatly restricts real-time autonomous navigation based on X-ray pulsars. To resolve this issue, a new method based on frequency subdivision and the continuous Lomb periodogram （CLP） is proposed to improve precision of period estimation using short-time observation data. In the proposed method, an initial frequency is first calculated using fast Lomb periodogram. Then frequency subdivision is per- formed near the initial frequency to obtain frequencies with higher precision. Finally, a refined period is achieved by calculating the CLP in the obtained frequencies. Real data experiments show that when observation time is shorter than 135 s, the proposed method improves period estimation precision by 1-3 orders of magnitude compared with the fast Lomb periodogram and fast Fourier transform （FFT） methods, with only a slight increase in computational complexity. Furthermore, the proposed method performs better than efsearch （a period estimation method of HEAsoft） with lower computational complexity. The proposed method is suitable for estimating periods of X-ray pulsars and obtaining the rotation period of variable stars and other celestial bodies.
基金Supported by the National Natural Science Foundation of China (Grant No. 10373017)
文摘Using the Lomb-Scargle periodogram we analyzed two sunspot series: the one over the past 11000 years at the 10-year interval based upon the survey data of 14C concentration in tree-rings, recon- structed by Solanki et al.; and the sunspot number over the past 7000 years, derived from geomagnetic variations by Usoskin et al. We found the periods and quasi-periods in solar activity, such as about 225, 352, 441, 522 and 561 a, and near 1000 and 2000 a. An approach of wavelet transform was applied to check the two sunspot time series, with emphasis on investigating time-varying characteristics in the long-term fluctuations of solar activity. The results show that the lengths and amplitudes of the periods have changed with time, and large variations have taken place during some periods.
