共查询到20条相似文献，搜索用时 437 毫秒
1.
结合钟差数据的特点,提出了一种基于变化率的T-S模糊神经网络(TSFNN)钟差预报模型。首先计算相邻历元间钟差的变化率值并对其进行建模;然后利用TSFNN模型预报钟差变化率值,再将预报的变化率值还原,得到钟差预报值;最后,通过算例将本文所建模型与IGU-P产品、二次多项式模型(QP)及灰色模型(GM(1,1))进行试验对比。结果表明:在使用变化率方法后,TSFNN模型预报的精度和稳定性分别提高了69.8%和76.3%,而且与IGU-P钟差产品相比,预报的精度高出约10倍,同时模型预报的效果优于两种常用模型。因此,该模型可以实现卫星钟差较高精度的预报。 相似文献
2.
Real-time clock offset prediction with an improved model 总被引：5，自引：3，他引：2
The GPS orbit precision of the IGS ultra-rapid predicted (IGU-P) products has been remarkably improved since 2007. However, the satellite clock offsets of the IGU-P products have not shown sufficient high-quality prediction to achieve sub-decimeter precision in real-time precise point positioning (RTPPP), being at the level of 1–3 ns (30–90 cm) RMS in recent years. An improved prediction model for satellite clocks is proposed in order to enhance the precision of predicted clock offsets. First, the proposed prediction model adds a few cyclic terms to absorb the periodic effects, and a time adaptive function is used to adjust the weight of the observation in the prediction model. Second, initial deviations of the predictions are reduced by using a recomputed constant term. The simulation results have shown that the proposed prediction model can give a better performance than the IGU-P clock products and can achieve precision better than 0.55 ns (16.5 cm) in real-time predictions. In addition, the RTPPP method was chosen to test the efficiency of the new model for real-time static and kinematic positioning. The numerical examples using the data set of 140 IGS stations show that the static RTPPP precision based on the proposed clock model has been improved about 22.8 and 41.5 % in the east and height components compared to the IGU-P clock products, while the precisions in the north components are the equal. The kinematic example using three IGS stations shows that the kinematic RTPPP precision based on the proposed clock model has improved about 30, 72 and 44 % in the east, north and height components. 相似文献
3.
为了提高卫星钟差预报的精度,针对小波神经网络(WNN)模型未能根据实际情况选取合适的小波函数的问题,本文提出一种基于"Shannon熵-能量比"的优选小波函数的小波神经网络钟差预报模型。首先利用小波函数对钟差一次差分数据进行连续小波变换,得到变换后的小波系数。然后分别计算小波系数的能量值和Shannon熵值,将"Shannon熵-能量比"(SEE)作为最优小波函数选择的评价指标,以指导选择最适合的小波函数作为WNN模型的激活函数。最后利用优选的WNN模型对卫星钟差进行预报,对预报的结果进行对比分析。结果表明:该评价指标能够根据卫星钟差实际情况准确指导WNN模型选择合适的小波函数,提高WNN模型的预报精度和适用性,使该模型可以实现卫星钟差较高精度的预报。 相似文献
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针对IGS超快星历钟差预报产品(IGU-P)精度较低及无法满足高精度实时PPP定位精度的问题,提出了一种GPS IIR-M型卫星超快星历钟差预报的高精度修正方法。该方法对预报值的第一个数据与IGU观测部分(IGU-O)数据的最后一个历元做差,根据差值对整个IGU-O差分序列的影响程度来确定精度修正的大小和方向,从而实现IIR-M型卫星高精度预报的效果。经过IGU实测数据的测试结果表明,在短期预报6 h范围内,本文提出的精度修正方法可使3种预报方案在原有预报精度基础上分别提升6.13%、3.9%和3。48%,预报精度分别控制在0.599 ns、0.570 ns和0.531 ns,且均优于IGU-P产品预报精度。 相似文献
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为了提高卫星钟差预报的精度,针对钟差数据中量级较小的误差,提出了一种基于中位数的小波阈值法钟差数据预处理策略。首先,利用小波阈值方法将钟差数据进行分解,得到分解后的高频系数和低频系数。然后,利用中位数法处理各层影响阈值设置的高频系数,通过处理后的高频系数计算阈值,从而提高小波阈值法剔除小异常值的能力。最后,用北斗二号卫星钟差数据进行了验证,结果表明,利用所提方法处理后的钟差数据建模,小波神经网络（wavelet neural network,WNN）模型预报的精度提高约14.1%,预报稳定性提高约19.7%。该方法可以有效剔除钟差历史观测序列中量级较小的误差,改善钟差数据质量,从而提高模型钟差预报的精度。 相似文献
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BDS星载原子钟长期性能分析 总被引：2，自引：2，他引：0
北斗卫星导航系统(BDS)于2012年底开始提供区域服务,进行BDS星载原子钟的长期性能分析,对于系统性能的评估、卫星钟差的确定与预报等具有重要的作用。本文基于3年的多星定轨联合解算的BDS精密卫星钟数据,利用改进的中位数方法进行数据预处理,分析了卫星钟差数据的特点,使用卫星钟差二次多项式拟合模型分析了卫星钟的相位、频率、频漂及钟差模型噪声的长期变化特性,根据频谱分析的方法分析了卫星钟差的周期特性,采用重叠哈达玛方差计算并讨论了卫星钟的频率稳定性。综合上述方法及其试验结果较为全面地分析和评估了BDS星载原子钟的长期性能,得到结论:在噪声特性和钟漂特性方面,MEO卫星钟的性能最好,其次是IGSO卫星钟,最差的是GEO卫星钟,所有卫星钟噪声水平和频漂的均值分别为0.677ns和1.922×10~(-18);多星定轨条件下的北斗卫星钟差存在显著的周期项,其主周期分别近似为对应卫星轨道周期的1/2倍或1倍;BDS星载原子钟频率稳定度的平均值为1.484×10~(-13)。 相似文献
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顾及卫星钟随机特性的抗差最小二乘配置钟差预报算法 总被引：2，自引：2，他引：0
为了更好地反映钟差特性并提高其预报精度,采用抗差最小二乘配置方法建立一种能够同时考虑星载原子钟物理特性、钟差周期性变化与随机性变化特点的钟差预报模型。首先使用附有周期项的二次多项式模型进行拟合提取卫星钟差的趋势项与周期项,然后针对剩余的随机项及其可能存在的粗差,采用抗差最小二乘配置的原理进行建模,其中最小二乘配置的协方差函数通过对比协方差拟合的方法并结合试验进行确定。使用IGS精密钟差数据进行预报试验,将本文方法与二次多项式模型、灰色模型进行对比,预报精度分别提高了0.457 ns和0.948 ns,而预报稳定性则分别提高了0.445 ns和1.233 ns,证明了本文方法能够更好地预报卫星钟差,同时说明本文的协方差函数确定方法的有效性。 相似文献
8.
The international GNSS service (IGS) has been providing an open-access real-time service (RTS) since 2013, which allows users to carry out real-time precise point positioning (RT-PPP). As the availability of RTS products is vital for RT-PPP, a disruption in receiving RTS products will be a concern. Currently, the IGS Ultra-rapid (IGU) orbit is accurate enough to be used as an alternative orbit for RTS during RTS outages, while the precision of the IGU predicted clock offsets is far below that of the RTS clock product. The existing clock prediction methods based on received RTS clock data will not work well if the discontinuity arises shortly after the start of the RT-PPP processing due to the lack of RTS clock data to fit the prediction model or to predict clock offsets at a high precision. Even if there is a sufficient amount of RTS clock data available, saving large amounts of RTS clock data would also use processor memory. An alternate approach for GPS clock prediction is proposed. The prediction model, composed of linear polynomial and sinusoidal terms, is similar to those used by the precious methods. The main innovation is the determination of the model coefficients: coefficients of linear and sinusoidal terms are estimated with the epoch-differenced clock offsets from the IGU observed part, while the constant coefficient is computed with the latest RTS clock corrections. There is no need to save the received RTS clock corrections, and clock prediction can be carried out even with only one epoch of RTS data. Evaluation of the proposed method shows that the predicted clock offsets within a short period of prediction time, e.g., 5 min, are slightly worse than RTS clock data. Even when the predicted time reaches up to 1 h, the precision of the predicted clock offsets is still higher than that of IGU predicted clock offsets by about 50%. 相似文献
9.
利用最小一乘法改进的灰色模型的导航卫星钟差预报 总被引：1，自引：0，他引：1
在卫星钟差波动较大的情况下,为了克服基于最小二乘法估计灰色模型参数对卫星钟差预报精度的不足,本文利用最小一乘法对传统灰色模型进行了改进。在建模的过程中,采用以误差绝对值之和最小为优化原则,针对目标函数不可微的特点,运用线性规划的方法对灰色预报模型的模型参数进行了估计。此外,将改进后的预报模型应用到卫星钟差波动较大情况下钟差的预报中,并将预报结果与传统灰色模型的预报结果进行了对比分析。结果表明：在卫星钟差波动较大的情况下,该方法相比传统灰色模型的预报结果有显著改善,为高精度的卫星钟差预报提供了一种新思路。 相似文献
10.
实时卫星钟差（satellite clock bias,SCB）的获取是实时精密单点定位（real-time precise point positioning,RTPPP）需要解决的关键问题。给出了国际GNSS服务（International GNSS Service,IGS）所提供的实时服务（real-time service,RTS）钟差产品的修复方法,分析了IGS02、IGS03实时数据流中GPS卫星钟差改正数的稳定性及其精度。同时,从原理上推导证明了钟差一次差分数据符合一次多项式模型,并结合对GPS卫星钟差改正数的分析提出了一种基于一次差分的钟差改正数预报算法,通过与一次多项式模型、二次多项式模型以及灰色模型的预报精度进行对比试验,结果表明,该钟差改正数预报算法预报精度有明显提高,预报30 s的精度达到0.06 ns,可满足实时精密单点定位的要求。 相似文献
11.
针对传统中位数绝对偏差（median absolute deviation,MAD）方法在探测钟差粗差方面的不足,提出一种改进的MAD钟差粗差探测方法。以一次差分数据为研究对象,通过深入分析传统MAD方法的工作原理,发现传统MAD方法的数学模型表达存在歧义。在优化探测模型结构的基础上,基于岭回归的基本原理,生成动态MAD,有效克服了部分具有显著趋势变化特征的钟差一次差分数据对粗差探测的干扰。使用国际全球卫星导航系统服务组织提供的GPS精密钟差数据进行了实验,并与传统MAD方法进行比较,结果表明,所提方法相较于传统的MAD方法在粗差探测准确率和查全率方面具有明显优势,实际应用价值较高。 相似文献
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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。 相似文献
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针对实时精密单点定位(RT-PPP)中实时数据流存在中断、延迟等问题,该文构建了顾及卫星钟自相关的随机模型,提出了一种基于方差分量估计的自适应卡尔曼滤波钟差超短期/短期预报算法,评估了连续27d实测法国空间研究中心(CNES)实时数据流CLK93产品完整率和精度水平,利用哈达玛方差对比分析了该实时产品与德国地学研究中心(GFZ)事后GBM产品的频率稳定性。利用本文算法与传统卡尔曼算法对两类产品进行预报,结果显示:CLK93产品BDS系统(C)、GPS系统(G)、GLONASS系统(R)、Galileo系统(E)30s和1min预报精度分别平均提升了8.50%、8.44%、7.20%、6.96%;GBM产品相应4个系统12h和24h预报精度分别平均提升了3.14%、3.53%、0.96%、10.01%。 相似文献
15.
Weixing Zhang Yidong Lou Shengfeng Gu Chuang Shi Jennifer S. Haase Jingnan Liu 《GPS Solutions》2016,20(4):665-676
We present the joint estimation model for Global Positioning System/BeiDou Navigation Satellite System (GPS/BDS) real-time clocks and present the initial satellite clock solutions determined from 106 stations of the international GNSS service multi-GNSS experiment and the BeiDou experimental tracking stations networks for 1 month in December, 2012. The model is shown to be efficient enough to have no practical computational limit for producing 1-Hz clock updates for real-time applications. The estimated clocks were assessed through the comparison with final clock products and the analysis of post-fit residuals. Using the estimated clocks and corresponding orbit products (GPS ultra-rapid-predicted and BDS final orbits), the root-mean-square (RMS) values of coordinate differences from ground truth values are around 1 and 2–3 cm for GPS-only and BDS-only daily mean static precise point positioning (PPP) solutions, respectively. Accuracy of GPS/BDS combined static PPP solutions falls in between that of GPS-only and BDS-only PPP results, with RMS values approximately 1–2 cm in all three components. For static sites, processed in the kinematic PPP mode, the daily RMS values are normally within 4 and 6 cm after convergence for GPS-only and BDS-only results, respectively. In contrast, the combined GPS/BDS kinematic PPP solutions show higher accuracy and shorter convergence time. Additionally, the BDS-only kinematic PPP solutions using clock products derived from the proposed joint estimation model were superior compared to those computed using the single-system estimation model. 相似文献
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由于卫星钟存在频率高、敏感性强、极易受到外界影响从而导致观测数据波动大,预测结果精度低的问题,利用幂函数变换法对初始观测数据进行变换预处理,从而提高观测数据的平顺度.由此提出一种基于幂函数变换的GM(1,1)模型,选用北斗卫星导航系统(BDS)卫星钟差进行插值和预报,并且进行了精度验证.实验结果表明:Lagrange插值方法可以满足高精度BDS的钟差的插值需要;利用幂函数变换的GM(1,1)模型相比传统模型精度有效提高了,而且当改进模型和传统模型预报值越接近实际值,则幂函数改进的GM(1,1)模型精度更高,适用性更强,对BDS卫星钟差预报具有实际参考价值. 相似文献
18.
Maintaining real-time precise point positioning during outages of orbit and clock corrections 总被引：1，自引：1，他引：0
The precise point positioning (PPP) is a popular positioning technique that is dependent on the use of precise orbits and clock corrections. One serious problem for real-time PPP applications such as natural hazard early warning systems and hydrographic surveying is when a sudden communication break takes place resulting in a discontinuity in receiving these orbit and clock corrections for a period that may extend from a few minutes to hours. A method is presented to maintain real-time PPP with 3D accuracy less than a decimeter when such a break takes place. We focus on the open-access International GNSS Service (IGS) real-time service (RTS) products and propose predicting the precise orbit and clock corrections as time series. For a short corrections outage of a few minutes, we predict the IGS-RTS orbits using a high-order polynomial, and for longer outages up to 3 h, the most recent IGS ultra-rapid orbits are used. The IGS-RTS clock corrections are predicted using a second-order polynomial and sinusoidal terms. The model parameters are estimated sequentially using a sliding time window such that they are available when needed. The prediction model of the clock correction is built based on the analysis of their properties, including their temporal behavior and stability. Evaluation of the proposed method in static and kinematic testing shows that positioning precision of less than 10 cm can be maintained for up to 2 h after the break. When PPP re-initialization is needed during the break, the solution convergence time increases; however, positioning precision remains less than a decimeter after convergence. 相似文献
19.
Three functional models, polynomial, spectral analysis, and modified AR model, are studied and compared in fitting and predicting clock deviation based on the data sequence derived from two-way satellite time and frequency transfer. A robust equivalent weight is applied, which controls the significant influence of outlying observations. Some conclusions show that the prediction precision of robust estimation is better than that of LS. The prediction precision calculated from smoothed observations is higher than that calculated from sampling observations. As a count of the obvious period variations in the clock deviation sequence, the predicted values of polynomial model are implausible. The prediction precision of spectral analysis model is very low, but the principal periods can be determined. The prediction RMS of 6-hour extrapolation interval is 1 ns or so, when modified AR model is used. 相似文献
20.
卫星钟差单差的小波神网络预报 总被引：2，自引：0，他引：2
针对现有卫星钟差预报模型对非平稳过程预报的局限性,提出基于卫星钟差一次差值的小波神经网络预报模型。对在轨卫星钟差求取一次差值的基础上,运用小波神经网络模型预报GPS卫星钟差,同时与GM(1,1)模型预报的结果进行比较。得出BlockΠA Cs短期预报的精度能达到0.690ns,14d预报的精度最差时依然优于1ns;其余稳定性良好的卫星钟,一天预报的结果均要优于0.207ns,预报14d卫星钟差的平均精度优于0.183ns,部分卫星钟差预报精度可以达到0.050ns,预报得到的结果可以达到GPS对实时精密单点定位的要求。 相似文献