...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Advances in space research >Development of multivariate ionospheric TEC forecasting algorithm using linear time series model and ARMA over low-latitude GNSS station
【24h】

Development of multivariate ionospheric TEC forecasting algorithm using linear time series model and ARMA over low-latitude GNSS station

机译：基于线性时间序列模型和ARMA的低纬度GNSS多元电离层TEC预测算法的开发

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Forecasting of ionospheric time delays has become a significant importance in satellite based navigation and communication system applications. Several researchers have been developed and implemented univariate Total Electron Content (TEC) forecasting models successfully over low, mid and high latitude regions. Therefore, identifying an effective multivariate forecasting technique is very essential to alert the Global Navigation Satellite System (GNSS) users under various space weather conditions. In this paper, a new multivariate ionospheric TEC forecasting model based on linear time series model in combination with Autoregressive and Moving Average (ARMA) is proposed and implemented using Bengaluru International GNSS Service (IGS) station data (geographic lat. -13.02 degrees N, long. 77.57 degrees E; geomagnetic latitude: 4.4 degrees N) during the period of 8 years (2009-2016) in the 24th solar cycle. The major factors, namely, geomagnetic activity (Ap), solar Extreme Ultraviolet (EUV) irradiance (F10.7p), periodic oscillations (annual, semi-annual, terannual and biennial oscillations) and long-term trend are considered in the model as input parameters along with real time TEC observations. The proposed model is twofold: first, the impact of solar, geomagnetic, trend and periodic factors on TEC has been investigated from linear model. Second, ARMA method is applied for forecasting each factor. The forecasted individual factors are combined to obtain the forecasted TEC values. The estimated TEC from the proposed model has good agreement with the observed Global Positioning System (GPS) - TEC. It is noticed that the magnitudes of semi-annual variation have been reflected to be high during the High Solar Activity (HSA) period. It is also found that the geomagnetic effect on TEC is relatively low. The proposed multivariate ionospheric TEC forecasting model would be useful for characterizing the low-latitude ionospheric variations under various space weather conditions. (C) 2018 COSPAR. Published by Elsevier Ltd. All rights reserved.
机译：电离层时间延迟的预测在基于卫星的导航和通信系统应用中已变得非常重要。已经开发了一些研究人员，并成功地在低，中和高纬度地区实施了单变量总电子含量（TEC）预测模型。因此，确定有效的多元预测技术对于在各种空间天气条件下向全球导航卫星系统（GNSS）用户发出警报都是非常重要的。本文提出了一种新的基于线性时间序列模型并结合自回归和移动平均值（ARMA）的多元电离层TEC预测模型，并利用班加罗尔国际GNSS服务（IGS）台站数据（北纬-13.02度，在第24个太阳周期的8年（2009-2016年），东经77.57度；地磁纬度：北纬4.4度。在模型中考虑了主要因素，即地磁活动（Ap），太阳极端紫外线（EUV）辐照度（F10.7p），周期性振荡（每年，半年，每半年和每两年一次的振荡）和长期趋势。输入参数以及实时TEC观测值。所提出的模型有两个方面：首先，从线性模型研究了太阳，地磁，趋势和周期性因素对TEC的影响。其次，将ARMA方法用于预测每个因素。将预测的各个因素合并以获得预测的TEC值。根据提议的模型估算的TEC与观测到的全球定位系统（GPS）-TEC有着很好的一致性。注意，在高太阳活动（HSA）期间，半年变化的幅度已反映为高。还发现地磁对TEC的影响相对较低。提出的多元电离层TEC预测模型将有助于表征各种空间天气条件下的低纬度电离层变化。 （C）2018年COSPAR。由Elsevier Ltd.出版。保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号