引潮位的Doodson规格化展开及其精度评定

基于引潮位Doodson规格化展开的基本原理以及ELP/MPP02月球历表、Newcomb太阳历表的结构,设计了一个用以代表三角函数的数据结构;并由此自定义了三角函数的乘法与加法算法,将月球、太阳引潮位分别展开至5阶、3阶,振幅绝对值截断阈值为10-7,在展开过程中对"伪波"进行"滤波"处理后,最终得到包含4 686项展开式的引潮位展开表(其中振幅绝对值超过10-6的展开式有2 441项)。以德国BFO(Black Forest Observatory)测站为例,基于DE431历表,通过天球参考系变换计算得到1950—2050年间时间间隔为1 h的法向引潮力基准序列BFDE431;并根据各个引潮位展开表计算得到相应的法向引潮力序列;通过与BFDE431基准序列求差,得到各个差值序列的统计值。计算结果表明,文中给出的展开表对应的差值序列数值在±58×10~(-11)m·s~(-2)(nGal)以内,均方差为12.5×10~(-11)m·s~(-2),与XI89展开表的精度相当。但由于没有考虑行星及地球扁率的影响,仍未达到HW95和RATGP95展开表的精度水平。     

无旋转倾角的NAV/CNAV型GEO广播星历拟合

目前北斗GEO的星历拟合算法和用户卫星位置算法均引进了人为设置的5°倾角旋转,此外,少数星历参数还有超限现象。取消GEO的旋转倾角和抑制参数超限能够统一北斗混合星座的用户算法。基于第一类无奇点根数,分析了无旋转倾角的GEO两步法星历参数拟合算法。讨论了GEO的参数超限原因,提出采用固定1至2个超限参数取值的缩减参数拟合法。北斗GEO卫星在非地影期和地影期的拟合试验表明,拟合成功率和拟合精度能够保证,拟合用户距离误差(URE)的平均值优于3mm;缩减参数拟合法能够抑制特定时段下的参数超限问题,但是拟合URE放大到2cm。     

自主导航星上快速星历拟合算法研究

针对北斗卫星导航系统地面监测站布设范围有限,系统抗打击能力不足等问题,我国已计划实现卫星自主导航。通过地面演示验证发现,星上自主定轨与时间同步软件同星上广播星历拟合软件耗费同等的机时。该文的研究目标为在保证精度的前提下,降低星上自主星历拟合的计算量。通过试验分析表明,采用直接降低星历参数个数的方法,会损失精度,效果不佳。利用自主导航自身特点,以长期预报星历为基础,通过参数固定,可在保证精度的基础上使矩阵求逆运算量降低近6倍。以长期预报星历为初值,可有效降低迭代次数,使计算量下降近5倍。     

IGS超快星历对GPS近实时反演水汽精度的影响研究

将IGS发布的超快星历与最终星历中卫星的坐标及钟差进行对比,初步验证IGS超快星历的精度。在此基础上,以美国国家海洋和大气局ARM实验中GPS连续运行参考站一周的观测数据作为实验对象,利用Bernese软件分别使用IGS最终星历以及超快星历进行GPS反演大气水汽含量的数据解算,将得到的基线精度以及对流层延迟值进行对比,结果表明采用最终星历和超快星历得到的基线精度基本相同,但对流层延迟值相差较大,并且差值较大的时刻一般出现在超快星历的外推时刻,并随着外推时间的增加逐渐增大。为此,本文设计了滑动式动态星历选择方案,通过实验验证,该优化方案能有效的提高近实时对流层延迟解算精度,满足GPS近实时反演大气水汽的精度要求。     

GPS广播星历参数拟合算法及其分析

利用地面观测资料定轨确定的卫星位置、进而计算出的卫星广播星历参数是进行卫星定位的基础。为了分析卫星星历拟合的精度和效率,推导了由卫星位置拟合GPS卫星广播星历参数的数学模型。并用算例分析了影响拟合效率的因素,分析了卫星位置有误差是对于卫星星历参数的影响。结果验证了所给出的算法的可行性和有效性。     

单组广播星历精度分析及其卫星轨道拟合研究

计算了单组广播星历外推2h时间内的精度,分析了精度的变化趋势,并基于广播星历对切比雪夫多项式拟合卫星轨道的方法进行了研究。     

基于IGS超快星历预报卫星钟差及其精度分析

在实时GPS精密单点定位中,能否快速有效地得到高精度的卫星钟差预报值是影响实时单点定位速度和精度的一个重要因素,由于GPS原子钟的高频率、高敏感和极易受到外界及其本身因素影响的性质使得卫星钟差预报至今都没能得到很好地解决,本文在目前的卫星钟差预报基础上,分别探讨了利用灰色模型理论、线性模型和二次多项式模型等方法,以IGS超快星历中2004年12月7日卫星钟差观测资料预报8日的卫星钟差为例进行卫星钟差预报研究,初步得出如下结论:在利用IGS超快星历的前一天的卫星钟差观测值预报后一天的钟差时,线性模型相对方便有效;而灰色模型只要选取合适的模型指数系数,能得到较高精度;但二次多项式模型预报精度较差。利用线性模型能达到或优于IGS超快星历预报钟差的预报精度。     

Quick Phase Identification for Dense Seismic Array with Aid from Long Term Phase Records of Co-located Sparse Permanent Stations

The phase identification and travel time picking are critical for seismic tomography, yet it will be challenging when the numbers of stations and earthquakes are huge. We here present a method to quickly obtain P and S travel times of pre-determined earthquakes from mobile dense array with the aid from long term phase records from co-located permanent stations. The records for 1 768 M ≥ 2.0 events from 2011 to 2013 recorded by 350 ChinArray stations deployed in Yunnan Province are processed with an improved AR-AIC method utilizing cumulative envelope and rectilinearity. The reference arrivals are predicted based on phase records from 88 permanent stations with similar spatial coverage, which are further refined with AR-AIC. Totally, 718 573 P picks and 512 035 S picks are obtained from mobile stations, which are 28 and 22 times of those from permanent stations, respectively. By comparing the automatic picks with manual picks from 88 permanent stations, for M ≥ 3.0 events, 81.5% of the P-pick errors are smaller than 0.5 second and 70.5% of S-pick errors are smaller than 1 second. For events with a lower magnitude, 76.5% P-pick errors fall into 0.5 second and 69.5% S-pick errors are smaller than 1 second. Moreover, the Pn and Sn phases are easily discriminated from directly P/S, indicating the necessity of combining traditional auto picking and integrating machine learning method.     

Experiments on Exploration of Shallow Fine Structures and the Construction of the 1-D Velocity Model in the Pingtan Island, Fujian

112 short-period seismographs were set up in the 400km² area of Pingtan Island and its surrounding areas in Fujian. The combined observations of the airgun source and ambient noise source were carried out using a dense array to receive the 387 airgun signals excited around the island and one month of continuous ambient noise recording. The 1-D P-wave and S-wave shallow velocity model of Pingtan Island is obtained by the inversion of the airgun body wave''s first arrival time data, and the reliability of the velocity model is verified by using the surface wave phase velocity dispersion curve, which can provide initial model for subsequent 3-D imaging. The experimental results show that this experiment is a successful demonstration of local scale green non-destructive detection, which can provide basic data for shallow surface structure research and strong vibration simulation of the Pingtan Island.     

GPS positioning accuracy using precise real‐time ephemeris and clock correction

Global positioning system (GPS) has found applications in various areas including marine geodesy. GPS positioning accuracy, however, is greatly degraded by GPS ephemeris and clock errors, particularly errors due to Selective Availability (SA). Thus, it is crucial to use precise ephemeris and clock corrections for users who require high position accuracy. Presently, precise ephemeris and clock corrections are available only in post‐mission. This paper investigates the generation of precise real‐time ephemeris and clock corrections and the positioning accuracy using them. In this research, precise real‐time ephemeris is generated from accurate dynamic orbit prediction and clock corrections are calculated using instantaneous GPS measurements. Numerical analysis using data from an actual GPS tracking network is performed that indicates use of precise ephemeris and clock corrections can improve the positioning accuracy to the one meter level. This accuracy is attainable in real‐time as the precise real‐time ephemeris and clock corrections become available in the future.