摘要
全球导航卫星系统(global navigation satellite system,GNSS)超快速轨道作为实时或近实时定位的重要参数,其精度与时效性是亟待解决的关键问题。针对超快速轨道观测后期精度降低的现象,提出了一种基于轨道参数精度衰减因子(dilution of precision,DOP)的定轨精化模型。首先,基于定轨观测数据,利用赤池信息准则对DOP值预报模型进行构建与优选;然后,以DOP值为自变量建立其与轨道状态参数之间的函数模型;最后,将高精度预报的DOP值回代入函数模型实现观测后期轨道精度的提升。为验证轨道精化模型,分别对观测数据长度和函数模型进行分析,结果表明,基于1 d的观测数据进行轨道模型精化最优,且不同函数模型无明显差异。基于连续10 d的多系统超快速轨道实验表明,超快速轨道观测后期精化模型可提升轨道精度12.4%~22.0%。因此,该模型可实现对超快速观测轨道精化,对分析中心超快速轨道的改善具有重要意义。
For ultra-rapid orbits provided by the Global Navigation Satellite System(GNSS),the key parameters,accuracy and timeliness,must be taken into consideration for real-time and near real-time navigation and positioning applications.With reference to the low accuracy in observed orbits(last 3 hours),an improved model based on the orbit dilution of precision(DOP)values is proposed by building the function models between DOP values and the orbit accuracy.Firstly,the prediction model of the DOP values is set based on observations and Akaike information criterion.Secondly,the function model between orbit accuracy and DOP values is built.At last,the predicted DOP values with highly precision are taken into orbit correction model to improve the observed ultra-rapid orbit accuracy.With the comparison experiments,it is found that there is a correlation between the DOP values of orbit parameter and its precision,and the variation trend of DOP values can be fitted based on polynomial model.Furthermore,to verify the availability of improved model,two experiment schemes were designed from the aspect of the length of observations and prediction models.In addition,there are no significant differences of orbit correction for different function models.With 10-day orbit determination experiments,the results show that the observed ultra-rapid orbit errors,generated by insufficient observations,can be corrected by 12.4%-22.0%for the last 3 hours of the observed orbits.Thus,the observed ultra-orbit correction model of our proposed is meaningful and can improve the ultra-rapid orbit accuracy of GNSS analysis center.
作者
胡超
王潜心
毛亚
HU Chao;WANG Qianxin;MAO Ya(Key Laboratory of Land Environment and Disaster Monitoring,MNR,China University of Mining and Technology,Xuzhou 221116,China;School of Environment Science and Spatial Informatics,China University of Mining and Technology,Xuzhou 221116,China)
出处
《武汉大学学报（信息科学版）》
EI
CSCD
北大核心
2020年第1期28-37,共10页
Geomatics and Information Science of Wuhan University
基金
国家自然科学基金(41874039)
江苏省自然科学基金(BK20181361)
江苏省研究生科研与实践创新计划(SJCX18_0668).
关键词
精度衰减因子
超快速观测轨道
轨道精度
精化模型
dilution of precision
ultra-rapid observed orbit
orbit accuracy
improved model
