›› 2013, Vol. 33 ›› Issue (4): 71-75.doi: 10.3780/j.issn.1000-758X.2013.04.010

• 技术交流 • 上一篇    下一篇

一种高精度GPS卫星钟差预报方法

陶庭叶1,2,3,高飞1,李晓莉1   

  1. (1 合肥工业大学土木与水利工程学院,合肥 230009)(2 武汉大学卫星导航定位技术中心,武汉 430079)(3 安徽省北斗卫星导航重点实验室,合肥230088)
  • 收稿日期:2012-09-24 修回日期:2012-12-02 出版日期:2013-08-25 发布日期:2013-08-25
  • 作者简介:陶庭叶 1980年生,2010年获武汉大学大地测量学与测量工程专业博士学位,副教授,博士后。主要从事GPS高精度定位、变形监测方面的教学科研工作。
  • 基金资助:

    国土环境与灾害监测国家测绘局重点实验室开放基金(LEDM2010B08),合肥工业大学博士专项基金(2010HGBZ0564),精密工程与工业测量国家测绘地理信息局重点实验室开放基金(PF2012-2)资助项目

One Prediction Method for High-precision GPS Satellite Clock Error

TAO Ting-Ye1,2,3, GAO Fei1, LI Xiao-Li1   

  1. (1 School of Civil and Hydraulic Engineering, Hefei University of Technology, Hefei 230009)(2 GNSS Research Center,Wuhan University,Wuhan430079)(3 Beidou Key Laboratory of Anhui Province, Hefei 230088)
  • Received:2012-09-24 Revised:2012-12-02 Online:2013-08-25 Published:2013-08-25

摘要: 为了获得实时高精度GPS钟差,提出了采用快速星历建模进行短期预报。文章先对钟差数据提取趋势项,再利用傅里叶分析研究其周期特征以确定建模与预报时间段长度,最后利用径向基函数(Radial Basis Function,RBF)神经网络建模实时预报钟差。由于RBF神经网络用于非线性数据建模效果良好,在提取线性趋势项并合理确定建模周期后,该方法能够得到较好的预报结果。实际预报结果表明,文中方法得到的预报钟差精度高于超快速星历,能够满足分米级实时精密定位的要求。

关键词: 钟差预报, 快速星历, 径向基函数, 神经网络, 频谱分析, 全球定位系统

Abstract: In order to get clock products with high accuracy in real time, the rapid clock products were used to establish a short-term prediction model. First, the data batch was detrended by fitting and removing with polynomial. Then, the spectrum of residual after detrending was calculated with Fourier transformation. Thus, the modeling period and forecasting period can be confirmed with the periodic characteristics. After this, the RBF (Radial Basis Function) neural network was used to fit and forecast the clock errors. Since the RBF neural network was fit for nonlinear data modeling, this method can get better forecasting results after extracting linear trend and determining reasonable modeling data size. In fact, prediction results indicate that clock error products obtained by the proposed method are shown to have higher accuracy than the ultra-rapid products, and can satisfy decimeter accuracy positioning applications.

Key words: Clock error prediction, Rapid ephemeris, Radial basis function, Neural network, Spectrum analysis, Global position system