基于goce的高分辨率重力场模型的信号与误差评估

IF 0.9 Q4 REMOTE SENSING
T. Gruber, M. Willberg
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引用次数: 19

摘要

摘要通过信号度方差和与独立gnss水准大地水准面高度的比较,评估了近年来基于goce的高分辨率重力场模型的信号含量和误差水平。将这些模型的球谐序列信号与GOCE之前的EGM2008模型进行比较,以确定GOCE数据、改进的地表和高空重力数据以及建模方法的影响。信号分析的结果表明,在全球平均情况下,大约80%的差异是由于包含了GOCE卫星信息,而其余20%是由于改进的地面数据。将全球模式与gnss水准水准衍生的大地水准面高度进行比较表明,如果有高质量的地面重力数据集可用,那么从全球模式得到的1 cm大地水准面是可行的。考虑到GOCE现在在80至100公里的空间尺度上提供厘米精度的大地水准面,对于覆盖率较低的地区,几厘米到一分米的精度是可行的。与GNSS水准大地水准面高度的比较也是研究全球模式、精神水准和GNSS高度观测中可能存在的系统误差的好工具。利用大地水准面高差和大地水准面坡度差可以分别得出各区域数据集的结论。需要考虑这些结论以进行更精细的分析,例如,消除可疑的gnss平准数据,通过使用全方差-协方差矩阵和通过一致地对用于高分辨率重力场模型的各种数据源进行加权来改进全球建模。本文描述了应用程序,展示了这些大地水准面高度和大地水准面坡度差异在一些区域数据集上的结果,并对可能的误差来源和今后在这方面需要做的工作作出了结论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Signal and error assessment of GOCE-based high resolution gravity field models
Abstract The signal content and error level of recent GOCE-based high resolution gravity field models is assessed by means of signal degree variances and comparisons to independent GNSS-levelling geoid heights. The signal of the spherical harmonic series of these models is compared to the pre-GOCE EGM2008 model in order to identify the impact of GOCE data, of improved surface and altimetric gravity data and of modelling approaches. Results of the signal analysis show that in a global average roughly 80% of the differences are due to the inclusion of GOCE satellite information, while the remaining 20% are contributed by improved surface data. Comparisons of the global models to GNSS-levelling derived geoid heights demonstrate that a 1 cm geoid from the global model is feasible, if there is a high quality terrestrial gravity data set available. For areas with less good coverage an accuracy of several centimetres to a decimetre is feasible taking into account that GOCE provides now the geoid with a centimetre accuracy at spatial scales of 80 to 100 km. Comparisons with GNSS-levelling geoid heights also are a good tool to investigate possible systematic errors in the global models, in the spirit levelling and in the GNSS height observations. By means of geoid height differences and geoid slope differences one can draw conclusions for each regional data set separately. These conclusions need to be considered for a refined analysis e.g. to eliminate suspicious GNSS-levelling data, to improve the global modelling by using full variance-covariance matrices and by consistently weighting the various data sources used for high resolution gravity field models. The paper describes the applied procedures, shows results for these geoid height and geoid slope differences for some regional data sets and draws conclusions about possible error sources and future work to be done in this context.
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来源期刊
Journal of Geodetic Science
Journal of Geodetic Science REMOTE SENSING-
CiteScore
1.90
自引率
7.70%
发文量
3
审稿时长
14 weeks
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