电离层总电子数预报方法研究

针对电离层总电子数对于提高导航定位精度的重要性,该文采用2014年国际GPS服务公布的年积日为第1~10d的电离层总电子数为原始数据,以自回归模型、灰色系统模型、BP神经网络模型两两结合的方式完成建模和预报。通过比较不同纬度、不同预测天数的实验结果分析各模型预报精度及适用范围。结果表明,利用BP神经网络模型对AR模型的预测值进行补偿,在赤道处模型拟合的相对精度达到91.32%;残差范围控制在-1.0~0.8TECU内,预报残差最优可达到0.0TECU,从而证明了该方法可以提高电离层总电子数预报精度。     

120°E赤道电离异常区电子浓度总含量分析与预测

基于国际全球定位服务中心(International GPS Service,IGS)提供的120°E 上空1999-2009年IONEX格式电离层电子浓度总含量(TEC)资料,分析赤道电离异常驼峰区TEC峰值Inc和Isc的年变化和季节变化以及与太阳、地磁活动的相关性.在11年时间尺度上,Inc和Isc与太阳辐射P指数的日均值有较好的相关性(r=0.90和r=0.84),而与地磁活动指数Dst、Kp和Ap日均值的相关性均不好.驼峰区TEC峰值Inc和Isc都是在北半球春、秋季出现极大值,而且冬季值大于夏季值,即Inc呈现"半年异常"和"冬季异常"现象,我们认为Inc和Isc相似的半年变化特征是与赤道上空电离层电急流相关的东向电场半年变化导致的.利用支持向量回归方法构建了EIA指数的预报模型,预报试验结果表明,该预报模型能较准确地描述Inc和Isc的变化,对南北驼峰TEC峰值预报的平均相对误差分别为22.96%和10.2%.基于支持向量机回归的预测方法为赤道电离异常特征指数预报的实现提供一条有效方法途径和好的应用前景.     

Analysis of the bias between TOPEX and GPS vTEC determinations

The TOPEX/Poseidon satellite was jointly developed and deployed by the National Aeronautics and Space Administration (NASA), USA, and the Centre National d’Etudes Spatiales (CNES), France (for details see Chelton et al. In: Fu L-L, Cazenave A (eds) International geophysics series, vol 69, ISBN 0-12-269545-3, Academic Press, CA, pp 1–131, 2001), with the main scientific goal of sea surface height monitoring. The process that ends with the TOPEX main observable (the range between the satellite and the sea surface) involves the measurement of several parameters of the radar pulses reflected by the sea surface and the computation of several other corrections. After several calibration campaigns performed by the Calibration/Validation team of the mission, it was found that TOPEX range determinations were systematically shorter than expected and it was decided to add an empirical correction of +15 mm to the TOPEX range-computation algorithm. As a by-product, TOPEX provides vertical total electron content (vTEC) determinations which have turned out to be a very important data source for the ionospheric research community. Since TOPEX vTEC measurements became available, several comparison studies have detected a constant bias, from +2 to +5 TECu, when TOPEX is compared to other vTEC sources, e.g., Global Positioning System (GPS), Doppler Orbitography and Radio-positioning Integrated by Satellite (DORIS), (TOPEX always greater than the others). In this work, we show that miscalibration of the corrections used in the TOPEX processing algorithm can cause the shortening effect of TOPEX ranges and at the same time the constant bias on the TOPEX vTEC values. It is also shown that changes on TOPEX System Biases of less than 10 mm for the Ku-band and between 40 and 70 mm for the C-band, can make both effects disappear. The analyzed hypothesis is supported by theoretical considerations and data analysis available in the specialized literature. On behalf of the authors of the contribution ‘Analysis of the bias between TOPEX and GPS vTEC determinations’, I declare that the paper has not been, nor is in the process of being published in any other publication.     

电离层TEC对小耀斑的响应

利用国际GPS观测网(IGS)提供的多个台站的观测数据,分析了M级别以下的小、暗太阳耀斑对向阳面电离层TEC的影响．利用传统分析方法的结果表明,从单条视线(LOS)观测数据得到的电离层TEC及其时间变化率曲线来看,由于它们的波动水平和正常情况下的背景电离层变化相当,使此类小耀斑的信息完全淹没在背景噪声中,不能够显示和分辨出耀斑的发生．利用相干求和的数据处理方法,选用向阳面18个GPS台站的观测数据研究了一次C级SF耀斑引起的电离层TEC增加,结果发现,这种方法能有效地消除背景电离层变化噪声,电离层对耀斑的响应非常清楚和明显,这通常只能在X级别的大耀斑中看到．和GOES卫星X射线数据相比,电离层TEC变化的时间特征和耀斑爆发的开始、最大和结束时间均有很好的符合,其最大平均TEC增量在0．1TECU以下,和X级别的大耀斑相比有一个或多个量级上的差别．     

利用神经网络预报短期电离层TEC变化

利用神经网络,基于IGS提供的(40°N,115°E)网格点TEC数据,本文构造了该点处提前一天的TEC预报模型。神经网络模型的预测目标是待预测日一天内的12个TEC数值。输入参数包括预测日前一日的太阳黑子数、地磁Kp指数、预测日前27天的太阳黑子数三角函数拟合参数,以及预测日前2天16个Kp指数的多项式拟合参数。实验结果表明训练后的神经网络模型可以反映出不同季节的TEC周日变化以及地磁暴情况下的TEC特征。     

Investigation of ionospheric TEC changes related to the 2008 Wenchuan earthquake based on statistic analysis and signal detection

Ionospheric TEC (total electron content) time series are derived from GPS measurements at 13 stations around the epicenter of the 2008 Wenchuan earthquake. Defining anomaly bounds for a sliding window by quartile and 2-standard deviation of TEC values, this paper analyzed the characteristics of ionospheric changes before and after the destructive event. The Neyman-Pearson signal detection method is employed to compute the probabilities of TEC abnormalities. Result shows that one week before the Wenchuan earthquake, ionospheric TEC over the epicenter and its vicinities displays obvious abnormal disturbances, most of which are positive anomalies. The largest TEC abnormal changes appeared on May 9, three days prior to the seismic event. Signal detection shows that the largest possibility of TEC abnormity on May 9 is 50.74%, indicating that ionospheric abnormities three days before the main shock are likely related to the preparation process of the M_S8.0 Wenchuan earthquake.     

2015年3月特大磁暴期间中国区域电离层TEC NeuralProphet预报模型研究

延迟是全球卫星导航定位中重要的误差源之一,提高电离层TEC建模和预报精度对改善卫星导航定位精度至关重要.本文构建了以太阳辐射通量指数F_10.7、地磁活动指数Dst、地理坐标和中国科学院(Chinese Academy of Sciences,CAS) GIM数据为输入参数的NeuralProphet神经网络模型(NP模型),实现在2015年3月特大磁暴期中国区域电离层TEC短期预报.为验证NP模型的预报精度,本文同时构建了长短期记忆神经网络(Long Short-term Memory Neural Network,LSTM)模型进行对比分析.结果统计分析表明,NP模型在磁暴期(2015年DOY076-078) TEC预报值RMSE和RD分别为0.83 TECU和3.13%,绝对和相对精度较LSTM模型分别提高1.49 TECU和10.25%;且NP模型RMSE优于1.5 TECU的比例达97.24%,远高于LSTM模型.NP模型预报值与CAS具有较好一致性和无偏性,偏差均值仅为-0.01 TECU,而LSTM模型预报值的均值偏大,偏差均值为1.49 TECU.从低纬到中纬度的三个纬度带内,NP模型RMSE分别为1.12、0.83和0.44 TECU,精度比LSTM模型提高1.94、1.56和1.23 TECU.整体上,在磁暴期NP模型预报性能明显优于LSTM模型,能够精细描述中国区域电离层TEC时空变化.

     

极区电离层TEC经验模型的建立及适用性分析

利用南极地区40多个GPS跟踪站2010年全年的实测数据,实现了极区电离层TEC建模,对多项式模型、广义三角级数函数模型、低阶球谐函数模型、改进的球谐函数模型以及球冠谐函数模型等五种电离层经验模型进行了比较,并评估了其在极区的适用性情况。结果表明,各个模型在极区都可以取得比较好的拟合精度,残差均值在0.1TECU以内,均方根误差在2 TECU以内。     

区域电离层TEC的变化研究

电离层延迟是影响全球卫星导航系统精密定位的主要误差源之一。本文介绍了常用的NeQuick模型和IRI模型,利用两模型进行了中国地区电离层TEC相关计算,将计算值与电离层参考值进行比较,得出了关于区域电离层TEC的有益结论。     

TEC浓度误差变化分析

电离层是大气层中的重要组成部分,但也是GPS测量误差中重要的影响因素,本文通过对电离层浓度分布研究,分析得出电离层的季节变化和在不同区域的变化趋势。