期刊文献+

一种基于三角分区的广域电离层改正新方法 被引量:3

A New Wide Area Ionospheric Correction Method Based on Triangular Partition
原文传递
导出
摘要 根据中国地形分布难以建立格网模型的特点,为了解决我国区域电离层精确改正的问题,提出了广域电离层改正三角分区的方法。选择中国地震电离层监测实验网中纬度地区的5个监测站,建立覆盖我国中纬度整个网络服务区域的三角分区电离层模型,并利用8个基准站的数据对该方法的修正精度进行评估,结果表明,对于三角分区内部区域,该方法可以修正到90%左右;对于三角分区外部几百公里以内的区域该方法也能达到80%以上的修正精度,同时利用原始GNSS数据对美国、加拿大等4个IGS跟踪站进行补充实验也验证了该方法的可行性,在保证模型精度的同时较格网法更加简单、有效,对广域电离层延迟误差的修正具有重要的参考价值。 Because of the characteristics of its topographic distribution, it is hard for China to set up a Grid-based ionospheric correction model. In order to obtain accurate regional ionospheric correction, the wide area ionospheric correction triangular partition method is proposed. A triangular partition of the ionospheric delay model for mid-latitude in China was established using five ionosphere reference stations of the China seismo-ionospheric groundbase monitoring network. The precision of the method was examined by eight reference stations, the results show that, in the case of the existing network layout for the triangular partition of the internal area, ionospheric delay error can be improved to 90% For the external triangular partition, hundreds of kilometers from the area, this method can al- so achieve correction accuracy of more than 80%. At the same time, GNSS data from four IGS track- ing stations in United States and Canada were used to test this method. The results also verify the fea- sibility of this method, with important reference value to the wide area single-frequency ionospheric delay error correction.
出处 《武汉大学学报(信息科学版)》 EI CSCD 北大核心 2015年第3期390-394,共5页 Geomatics and Information Science of Wuhan University
基金 国家自然科学基金资助项目(61263028) 广西自然科学基金资助项目(2012GXNSFDA053027) 中国科学院精密导航定位与定时技术重点实验室开放研究基金资助项目(2012PNTT04) 中国科学院时间频率基准重点实验室开放研究基金资助项目(y000yr1s01)~~
关键词 中纬度 TEC 电离层改正 三角分区法 模型精度 middle latitude total electron content (TEC) ionospheric correction~ triangular partitionmethod model accuracy
  • 相关文献

参考文献4

二级参考文献48

  • 1夏淳亮,万卫星,袁洪,余涛.磁暴期间电离层扰动的GPS台网观测分析[J].空间科学学报,2004,24(5):326-332. 被引量:8
  • 2谷志红,牛东晓,王会青.广义回归神经网络模型在短期电力负荷预测中的应用研究[J].中国电力,2006,39(4):11-14. 被引量:32
  • 3HABARULEMA J B, MCKINNELL L A, CILLIERS P J. Prediction of Global Positioning System Total Electron Content Using Neural Networks over South Africa [ J]. Journal of Atmospheric and Solar-Terrestrial Physics. 2007, 69: 1842-1850.
  • 4MCKINNELL L A, FRIEDRICH M. A Neural Networkbased Ionospheric Model for the Auroral Zone[J]. Journal of Atmospheric and Solar-Terrestrial Physics. 2007, 69:1203-1210.
  • 5FRIEDRICH M, EGGER G, MCKINNELL L A, et al. Perturbations in EISCAT Electron Densities Visualised by Normalisation[J]. Advances in Space Research. 2006, 38: 2413-2417.
  • 6Simon Haykin. Neural Network: A Comprehensive Foundation[M]. USA: Person Education. 1999,8: 183-201.
  • 7WANG Wei, FAN Guoqing, XI Xiaoning. Composite Data Weight Analysis of Ionosphere Model Determination[C]// The 2007 International Symposium on GNSS/GPS. Sydney:[s.n.], 2007: 16.
  • 8PARZEN E. On Estimation of a Probability Density Function and Mode[J]. Annals of Mathematical Statistics, 1962, 33: 1065-1076.
  • 9ROSENBLATT M. Density Estimates and Markov Sequences Nonparametric Techniques in Statistical Inference [M]. Cambridge: Cambridge Univ. Press, 1970, 41 :199- 213.
  • 10ROSENBLATT M. Remarks on Some Nonparametric Estimates of a Density Function[J]. Annals of Mathematical Statistics, 1956, 27, 832-837.

共引文献78

同被引文献23

引证文献3

二级引证文献5

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部