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幂函数变换的GM(1,1)模型在BDS卫星钟差预报中的应用研究
引用本文:蒋玉祥.幂函数变换的GM(1,1)模型在BDS卫星钟差预报中的应用研究[J].全球定位系统,2020,45(2):49-54.
作者姓名:蒋玉祥
作者单位:西宁市测绘院,青海西宁810001
摘    要: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.

关 键 词:GM(1  1)模型  幂函数变换  BDS卫星钟差  改进GM(1  1)模型  精度检验

Application research of GM(1,1) model of power function transform in BDS satellite clock bias prediction
JIANG Yuxiang.Application research of GM(1,1) model of power function transform in BDS satellite clock bias prediction[J].Gnss World of China,2020,45(2):49-54.
Authors:JIANG Yuxiang
Affiliation:Basic Surveying and Mapping Institute of Qinghai Province,Xining 810001, China
Abstract:Due to the high frequency, strong sensitivity of satellite clocks, and the extreme susceptibility to external influences, the observation data fluctuates greatly and the results have low accuracy.The power function transformation method is used to transform and preprocess the initial observation data to improve the smoothness of the observation data.Therefore, a GM (1,1) model based on power function transformation was proposed. The BDS satellite clock difference was used for interpolation and prediction, and the accuracy was verified. The experimental results show that the Lagrange interpolation method can meet the clock interpolation needs of high-precision BDS;The GM (1,1) model using power function transformation has effectively improved the accuracy compared to traditional models.And when the predicted values of the improved model and the traditional model are closer to the actual values,Then the improved GM (1,1) model of the power function has higher accuracy and stronger applicability. It has practical reference value for BDS satellite clock error prediction. 
Keywords:GM(1  1) model  power function transformation  BDS satellite clock difference  improved GM(1  1) model  accuracy test
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