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GPS在轨卫星原子钟的稳定性分析

导航卫星星载原子钟的相位或频率数据,作为导航系统应用研究的基础,将直接影响导航系统时间尺度建立以及定位的精度和准确性。本文针对由IGS官网提供的四种GPS卫星钟的钟差数据,采用修正阿伦方差进行了稳定性分析,得到了一些有益的结论。     

航空矢量重力测量中光纤陀螺随机漂移误差实时补偿方法

光纤陀螺随机漂移误差是影响航空矢量重力测量系统姿态解算精度的关键因素。建立模型并在输出中对其补偿是抑制该项误差的有效方法。针对传统ARMA模型只能对平稳随机漂移误差建模,且模型无法满足实时滤波需求的问题,本文引入适用于非平稳随机漂移误差的ARIMA模型,同时给出详细的建模过程,并提出采用实时平均算法消除原始采样序列中常值分量的思路,实现了随机漂移误差的实时Kalman滤波估计。基于本文所提出的模型和实时滤波算法,对光纤陀螺实测数据进行分析,结果表明处理后信号中随机漂移误差的方差减小了46.5%。Allan方差分析结果表明,滤波后角度随机游走系数和角速率随机游走系数分别降低了约50%和40%。本文的结果说明ARIMA模型能够准确描述陀螺的非平稳随机漂移误差。基于实时平均算法的Kalman滤波可实现随机漂移误差的在线估计,有望提高航空矢量重力测量系统的姿态解算精度。     

利用Allan方差分析GPS非差随机模型特性

非差GPS定位中,通常采用以观测值服从高斯白噪声条件的估计准则进行参数求解。研究表明卫星端误差、传播路径误差、测站环境误差等会破坏观测值的白噪声特性,并且未模型化误差同样具有不利影响。这不仅破坏了估计准则的假设条件,而且部分非白噪声有可能被状态参数吸收,影响估计的准确性。本文将观测值白噪声、有色噪声和未模型化误差一同纳入GPS非差随机模型,以验后残差来表征GPS数据的随机特性,进行Allan方差分析,研究噪声成分及其参数。结果表明,GPS非差噪声组合主要为WN+GM,相位白噪声为2.392mm,GM过程噪声为4.450mm/s,相关时间为52.074s,伪距白噪声为0.936m,GM过程噪声为0.833m/s,相关时间为14.737s,相位的GM过程噪声与卫星相关性较大,而其余噪声则与测站相关性较大,大量分析结果表明GPS非差随机模型并不服从高斯白噪声假设,有待精化。     

云闪辐射脉冲序列的丛集特征

根据2002年夏季那曲地区野外观测的宽带干涉仪资料, 应用变异系数CV、 Allan因子分析(AFA)和Fano因子分析(FFA)等统计方法, 对33个云闪辐射脉冲事件序列的时间丛集特征进行了分析.结果显示, 放电过程呈现强的分形丛集性, 变异系数平均为5.2, AFA和FFA标度指数αAF及αFF平均分别为1.42和0.81; 同时发现, 初始强K脉冲前CV增加到明显>1.     

Time-clustering behavior of spreading-center seismicity between 15 and 35°N on the Mid-Atlantic Ridge: observations from hydroacoustic monitoring

An earthquake catalog derived from the detection of seismically-generated T-waves is used to study the time-clustering behavior of moderate-size (?3.0 M) earthquakes between 15 and 35°N along the Mid-Atlantic Ridge (MAR). Within this region, the distribution of inter-event times is consistent with a non-periodic, non-random, clustered process. The highest degrees of clustering are associated temporally with large mainshock-aftershock sequences; however, some swarm-like activity also is evident. Temporal fluctuations characterized by a power spectral density P(f) that decays as 1/f^α are present within the time sequence, with α ranging from 0.12 to 0.55 for different regions of the spreading axis. This behavior is negligible at time scales less than ∼5×10³ s, and earthquake occurrence becomes less clustered (smaller α) as increasing size thresholds are applied to the catalog. A power-law size-frequency scaling for Mid-Atlantic Ridge earthquakes also can be demonstrated using the distribution of acoustic magnitudes, or source levels. Although fractal seismic behavior has been linked to the structure of the underlying fault population in other environments, power-law fault size distributions have not been observed widely in the mid-ocean ridge setting.     

星载原子钟稳定性影响分析

以最大限度保持星载原子钟稳定性计算结果的准确、可靠性为目标,分析了原始数据采样间隔、非连续间断时间序列、无数据段、频率漂移等因素对原子钟稳定性计算结果的影响。利用GPS卫星精密钟差数据针对阿仑和哈达玛方差进行了影响量级分析,得出了有益的结论。     

Monofractal and multifractal approaches in investigating scaling properties in temporal patterns of the 1983-2000 seismicity in the western Corinth graben, Greece

Much recent work has been focused on understanding the statistical properties of time-occurrence series of earthquakes. Investigating into the patterns of seismic sequences reveals evidence of scaling features in temporal behavior. This is shown in the clustering properties of seismicity of the western Corinth graben, Greece from 1983 to 2000. Power-law behavior has been found by means of Allan factor analysis and Fourier spectra for the earthquake sequence, with consistent values for the scaling exponents, that decrease with the threshold magnitude. The analysis of the temporal variation of the scaling exponent, performed with different threshold magnitudes, reveals an enhancing of the clusterization in correspondence to larger events. The multifractal analysis of the temporal distribution of the events has shown a decrease of the intermittent character with the threshold magnitude.     

Analysis of the time-scaling behaviour in the sequence of the aftershocks of the Bovec (Slovenia) April 12, 1998 earthquake

Analysis of the temporal fluctuations, described by a power spectral density S(f) decaying as 1/f with exponent >0, in the sequence of aftershocks of the Bovec (Slovenia) earthquake of April 12, 1998 has been performed, using the Allan Factor (AF) method. The sequence of the occurrence times of the events with threshold magnitude M_th≥2.0 is characterised by a scale-invariant behaviour from the time scale τ2·10⁴ s with a scaling coefficient 0.9, evaluated by a least-square method. By gradually increasing the threshold magnitude up to M_th=2.9, the AF curves, associated, respectively with the processes of selected events with magnitude M≥M_th, indicate a monotonic decrease of the value of the scaling exponent , in the range of time scales stretching from 10² to 5·10⁵ s. For all the thresholds considered, the AF curves increase monotonically with the counting time and are well fitted by an increasing power-law function for counting times greater than approximately 2·10⁴ s. This monotonic power-law increase indicates the presence of fluctuations on many time scales and therefore of fractal clustering.