武汉地区电离层TEC和NmF2及板厚的季节变化

通过利用武汉电离层观测站(114.4°E,30.6°N)1980-1990年对E8T-Ⅱ卫星信标的法拉第旋转测量的TEC(电子浓度总含量)数据,以及由测高仪测量的1980-1990年间的f0F2(F2层临界频率)数据,研究了武汉地区TEC,NmF2(最大电子浓度)和板厚的季节变化,同时比较了IRI和武汉单站模式在预测NmF2季节性方面的有效性.武汉单站模式在预测NmF2季节性变化方面优于IRI模式.      

通过GPS测量数据研究电离层电子总含量的逐日变化

提出了一种直接通过双频GPS伪距测量数据导出接收站附近垂直TEC的方法,这种方法不需要事先知道卫星和接收机电路时延的精确值,前者可在换算过程中自洽地加以修正,而接收机时钟误差则利用IRI模式的夜晚平均值作为参考来订正,这一订正存在一定的绝对误差,但不会影响逐日相对变化,却使数据处理过程大为简化.得到的垂直TEC为天顶周围60锥角内的平均值,能够相当好地反映电离层电子总含量的周日变化.一个计算实例显示了连续三天北京地区TEC的日变化情况,证实了这一方法的实用性.文中还提出一个新概念或问题,即GPS卫星仰角很小时,通常认为多径效应造成大的误差,本文的一些实例似乎表明,这种多径效应的概念应当包括电离层不规则结构的贡献.     

基于双频GPS观测的电离层TEC与硬件延迟反演方法

利用全球定位系统（Global Positioning System,GPS）的双频观测数据反演得到电离层的总电子含量（Total Electron Content,TEC）,使得广域甚至全球范围高时空分辨率的电离层观测研究成为可能,但由于GPS卫星和接收机对信号的硬件延迟可导致TEC测量系统偏差,因此,需要探索反演TEC并估测GPS卫星与接收机硬件延迟的有效算法.本文根据电离层电波传播理论,阐述了基于双频GPS观测提取电离层TEC的方法,给出TEC与硬件延迟的基本关系.综合研究了TEC与硬件延迟的反演方法,进行分析与归纳分类,在此基础上提出了有待深入研究的问题.      

赤道异常区GPS-TEC与系统硬件偏差的反演

提出了一种基于最小二乘的赤道异常区GPS-TEC与系统硬件偏差的反演方法.利用设置在福州、厦门、广州和南宁4个台站的观测数据,可以得到GPS卫星和接收机的硬件偏差以及(20°～28°N,105°～123°E)区域中48个3°×1°网格的TEC(时间分辨率为15 min).应用于2006年观测数据,得到了较稳定的系统硬件偏差,其中卫星硬件偏差值与欧洲定轨中心公布的结果接近,得到的TEC具有合理的日变化和季节变化特征.该反演方法可以应用于赤道异常区电离层的研究.      

IRI-2007预测TEC在广州地区的适用性分析

利用广州站(23.2°N, 113.3°E) GPS双频接收机监测的电离层TEC数据和IRI-2007模型不同电离层输入参数计算得到的TEC预测值, 对比分析了太阳活动低年(2008年)广州地区TEC的变化特征. 结果表明, TEC观测值周日变化在16:00LT左右达到最大值, 而IRI-TEC最大值出现时间较GPS-TEC提前1h左右. TEC季节变化在春秋分较高, 两至季节较低, 表现出明显的半年特性和季节依赖性, 并出现冬季异常现象. IRI-TEC与GPS-TEC在白天具有较好的一致性, 夜间偏差较大. 不同电离层输入参数得到的TEC预测值也相差较大, 选用顶部电子密度参数NeQuick、底部厚度参数B0 Table并用URSI系数计算F₂层峰值参数时, 能较好地反映TEC观测值的变化特征. 在对磁暴的响应上, 预测值无明显变化, 观测值则有比较明显的表现. 通过对比, 初步分析了利用IRI-2007模型预测TEC在广州地区的适用性, 并给出了合理的参数选择方案.      

基于北斗GEO卫星双频观测值连续监测电离层延迟

利用北斗GEO卫星观测数据直接计算电离层延迟。由于GEO卫星具有固定穿刺点和静地的特性,使得观测站监测电离层变化时可不考虑空间变化,并可进行连续不间断监测。通过分析北斗GEO卫星三种频率码伪距和载波相位观测值不同组合,选取B1&B2双频计算电离层延迟为最优组合,采用相位平滑伪距的方法计算电离层延迟TEC,相较其他电离层模型,该方法的优点是不会引入模型误差,可得到连续的高精度的电离层延迟监测结果。     

昆明上空电离层D区电子密度季节变化的首次观测分析

通过分析2008年8月至2009年7月昆明站(25.6°N, 103.8°E) 中频(MF)雷达观测数据, 研究了太阳活动低年电离层D区电子密度的季节变化特性,发现D区电子密度主要呈现半年变化特征, 即在春秋季电子密度较大, 而在夏冬季则较小, 这与国际参考电离层(IRI)预测的年变化趋势不一致, 但与昆明站电离层测高仪的最低回波频率f_min的观测结果相符. 同时比较了D区电子密度半年变化与纬向风半年变化的关系, 发现二者之间保持了非常一致的变化趋势并对这种一致性的内在原因进行了分析.      

VLF波从大气层到低电离层的传输特性分析

基于传播矩阵法计算了均匀半空间电离层的反透射系数, 同时解Booker复系数四次方程得到电离层的复折射指数, 分别研究了电离层反射透射系数及折射指数随VLF频段入射电波频率、入射角和地磁倾角、电离层电子浓度及碰撞频率的变化规律. 计算结果表明, 在VLF频段, 垂直电偶极子辐射的横磁(Traverse Magnetic)波更易透射进入电离层, 而水平电偶极子辐射的横电(Traverse Electric) 波易被限制在地-电离层波导内来回反射. 电离层电子密度较低时 (如夜间), 在高纬度地区, 观测到地震电离层VLF异常的概率更大. 当考虑地磁场 的影响时, 电离层将允许地震辐射的超低频(Ultra Low Frequency ,ULF)/甚低频 (Very Low Frequency, VLF)部分的电磁波透射进入电离层, 这一点已有很多卫星观测事实为证, 但其进一步的物理机制尚需深入研究.      

电离层Es电波传播模型研究

考虑大气折射的影响,对不同高度Es层条件下大圆路径传播距离与仰角的关系进行计算.基于电离层Es电子密度时空分布特点,建立高阶Es反射模型;运用高阶修正贝塞尔函数表示电离层Es电子密度扰动的自相关函数,综合考虑电离层Es各向异性结构的尺度关系,建立高阶Es散射模型.仿真计算Es层VHF斜入射传播衰减与频率、距离的关系.对于反射模型,Es层厚度越厚,电波衰减越大.对于散射模型,Es层不规则体水平尺度相同,垂直水平漂移的尺度越大,衰减越大;而垂直水平漂移的尺度相同,水平尺度越大,衰减越小.无论反射模型还是散射模型,f₀E_s越高,衰减越小;电波工作频率越高,衰减越大.对比建立的模型与VHF链路的测量结果,明确不同强度的电离层Es反射/散射机制,证明了建立模型的正确性.      

一种地基GNSS接收机差分码偏差估算方法

GNSS不同频点间的码伪距作差会引入信号的差分码偏差(DCB),包括GNSS卫星及地面接收机的DCB.本文提出一种地基GNSS接收机差分码偏差参数估算方法,首先由电离层文件参数作线性插值,计算出电离层延迟误差.之后对IGS站观测文件进行加权最小二乘法估计,得到GPS卫星和地面GNSS接收机的L1C频点和L2P频点间码偏...     

用Kriging方法构建中纬度区域电离层TEC地图

提出了中国中北部及周边(30°N～55°N,70°E～140°E范围内)区域电离层电子浓度总含量(TEC)地图(简称CNC TEC Map)的Kriging算法.比较了目前被广泛使用的电离层模型(Klobuchar,IRI和JPLGIM)与真实的TEC分布的符合情况;比较了常数漂移(普通Kriging方法)、线性漂移和二次漂移的Kriging方法;在三种不同的时间分辨率(5min,30min和120min)下,比较了Kriging算法、就近插值算法和多项式回归算法(5阶)绘制CNC TEC Map的效果.结果显示在本文研究区域内常用的电离层模型与真实TEC分布存在较大的区别;使用普通Kriging方法就可以较好的表示华北地区TEC分布;Kriging方法的结果优于其余两种插值算法,尤其是当时间分辨率提高到5 min时,Kriging算法的优势比较明显.      

太阳活动低年广州地区地磁扰动与电离层闪烁的统计特征分析

基于肇庆地磁台的地磁监测数据和广州气象卫星地面站建立的华南地区GPS电离层闪烁监测网的监测数据, 统计分析了2008年7月至2010年7月太阳活动低年期间广州地区地磁扰动与电离层闪烁的关系. 用肇庆台地磁水平分量H的变化量换算出肇庆地磁指数K, 以此来代表广州地区地磁扰动情况.分析结果表明, 磁暴/强地磁扰动对广州地区电离层闪烁的发生总体表现为抑制作用, 电离层闪烁主要发生在低K值期间, 而在K ≥ 4时电离层闪烁的发生呈下降趋势. 电离层闪烁发生率随季节和地磁活动的变化规律表现在, 春季的弱闪烁发生率、夜间中等以上闪烁发生率和夏季中等以上闪烁的发生率明显与地磁活动指数K相关, 即随$K$指数的增大而减小; 在秋季和冬季闪烁发生率与K指数变化无明显关系. 同时还综合分析了地磁与太阳活动的变化对电离层活动的影响, 广州地区闪烁主要发生在太阳活动较低的磁静日期间.      

基于BDS/GPS和经验模型的区域电离层建模

基于北斗卫星导航系统（BDS）和全球定位系统（GPS）实测电离层穿刺点（IPP）数据，结合国际参考电离层（IRI）经验模型历史数据，提出一种对区域二维电离层总电子含量（TEC）进行高精度建模的方法.针对缺乏穿刺点的区域内短时间电离层建模时精度较低且各时段穿刺点空间分布不同的问题，该方法使用IRI模型在建模区域内均匀添加虚拟穿刺点数据，并根据与实测穿刺点的距离，使用构造的权重计算公式赋予其动态权重值，通过加权最小二乘法进行球谐模型参数解算.与欧洲定轨中心（CODE）发布的全球电离层图（GIM）进行数据比对发现，相对于只使用BDS/GPS实测穿刺点数据的建模方法，利用本文建模方法计算获得的垂直总电子含量（VTEC）值对缺乏实测穿刺点的区域精度有明显的提升.      

Using GPS-TEC data to calibrate VTEC computed with the IRI model over Nigeria

This paper presents the development of a Total Electron Content (TEC) map for the Nigerian ionosphere. In this work, TEC measurements obtained from the AFRL-SCINDA GPS (Air Force Research Laboratory-Scintillation Network Decision Aid, Global Positioning System) equipment installed at Nsukka (6.87°N, 7.38°E) are used to adapt the International Reference Ionosphere (IRI) model for the Nigerian Ionosphere. The map is being developed as a computer program (implemented in the MATLAB programming language) that shows spatial and temporal representations of TEC for the Nigerian ionosphere. The method is aimed at showing how the IRI model can be used to estimate VTEC over wide areas by incorporating GPS measurements. This method is validated by using GPS VTEC data collected from a station in Ilorin (8.50°N, 4.55°E).     

Regional 4-D modeling of the ionospheric electron density from satellite data and IRI

Accurate knowledge of the electron density is the key point in correcting ionospheric delays of electromagnetic measurements and in studying ionosphere physics. During the last decade Global Navigation Satellite Systems (GNSS) have become a promising tool for monitoring ionospheric parameters such as the total electron content (TEC). In this contribution we present a four-dimensional (4-D) model of the electron density consisting of a given reference part, i.e., the International Reference Ionosphere (IRI), and an unknown correction term expanded in terms of multi-dimensional base functions. The corresponding series coefficients are calculable from the satellite measurements by applying parameter estimation procedures. Since satellite data are usually sampled between GPS satellites and ground stations, finer structures of the electron density are modelable just in regions with a sufficient number of ground stations. The proposed method is applied to simulated geometry-free GPS phase measurements. The procedure can be used, for example, to study the equatorial anomaly.     

A 12 year comparison of MIDAS and IRI 2007 ionospheric Total Electron Content

Data assimilation in conventional meteorological applications uses measurements in conjunction with a physical model. In the case of the ionised region of the upper atmosphere, the ionosphere, assimilation techniques are much less mature. The empirical model known as the International Reference Ionosphere (IRI) could be used to augment data-sparse regions in an ionospheric now-cast and forecast system. In doing so, it is important that it does not introduce systematic biases to the result. Here, the IRI model is compared to ionospheric observations from the Global Positioning System satellites over Europe and North America. Global Positioning System data are processed into hour-to-hour monthly averages of vertical Total Electron Content using a tomographic technique. A period of twelve years, from January 1998 to December 2009, is analysed in order to capture variations over the whole solar cycle. The study shows that the IRI model underestimates Total Electron Content in the daytime at solar maximum by up to 37% compared to the monthly average of GPS tomographic images, with the greatest differences occurring at the equinox. IRI shows good agreement at other times. Errors in TEC are likely due to peak height and density inaccuracies. IRI is therefore a suitable model for specification of monthly averages of Total Electron Content and can be used to initialise a data assimilation process at times away from solar maximum. It may be necessary to correct for systematic deviations from IRI at solar maximum, and to incorporate error estimation into a data assimilation scheme.     

A study on Nighttime Winter Anomaly (NWA) and other related Mid-latitude Summer Nighttime Anomaly (MSNA) in the light of International Reference Ionosphere (IRI) – Model

The ionospheric Nighttime Winter Anomaly (NWA) is a feature observed in the Northern Hemisphere at the American and in the Southern Hemisphere at the Asian longitude sector under low solar activity conditions. Jakowski et al. (2015) analyzed ground-based GPS derived TEC and peak electron density data from radio occultation measurements on Formosat-3/COSMIC satellites and confirmed the persistence of the phenomenon. Further, they assumed that Mid-latitude Summer Nighttime Anomaly (MSNA) and related special anomalies such as the Weddell Sea Anomaly (WSA) and the Okhotsk Sea Anomaly (OSA) are closely related to the NWA via enhanced wind-induced uplifting of the ionosphere. The aim of this paper is to study the factors causing these anomalies and also to investigate if these anomalies are re-produced by IRI. The results show that IRI model does include the NWA effect, though at a different longitude and could be improved for better predictions. The IRI-2016 model does show WSA in TEC but not in NmF2. Further, the IRI-2016 model could clearly predict the OSA both in NmF2 and TEC.     

电离层周日变化对解算GPS硬件延迟稳定性的影响

针对电离层周日变化特征分析了其可能对SCORE方法估算的硬件延迟稳定性的影响. 利用BJFS以及XIAM台站的GPS观测数据, 解算了位于太阳活动高年(2001年)和太阳活动低年(2009年)的卫星硬件延迟并分析了估算的硬件延迟的稳定性. 研究发现, 电离层周日变化对估算的硬件延迟稳定性具有一定影响, 但是利用不同台站所得到的卫星硬件延迟稳定性在昼夜不同时间上的解算结果存在一定差异. 电离层周日变化对利用 BJFS台站数据解算的硬件延迟稳定性日夜差异较为明显, 在太阳活动高年利用XIAM 台站数据解算的硬件延迟日夜稳定性差异不很明显, 由于XIAM台站处于电离层赤道异常峰附近, 夜间电离层变化很大, 因此对比中纬度地区, 电离层周日变化对赤道异常峰附近地区硬件延迟稳定性解算结果的影响相对较小, 但在太阳活动低年, 其影响仍较为显著.      

New field of application of the IRI modeling – Determination of ionosphere transfer characteristic for radio astronomical signals

We suggest a new field of application of IRI modeling – determination of ionosphere transfer characteristic (ITC) for radio astronomical signals (RAS). VHF and HF RAS are widely used for observations of the Sun and pulsars. It is necessary to take into account possible distortions of RAS in the Earth ionosphere. However, in contrast to modern navigation systems (GPS, GLONASS, GALILEO), where very accurate reconstruction of ionosphere parameters is a built-in function, in present-day radio astronomy a retrieve of ITC has not been appropriately worked out yet. It collides with increasing requirements to accuracy of the analysis of RAS amplitude profile and to the angular and polarizing resolution of radio telescopes of new generation. We have developed a method and software for calculation of the ionosphere measure of rotation (RM) and the measure of dispersion (DM). We used the ionosphere model IRI-2001, magnetic-field model IGRF-10 and values of ionosphere total electron content as deduced from GPS measurements. The obtained values of the ionosphere DM and RM were recalculated into characteristics of phase delay, Faraday amplitude modulation and polarization changes. We made calculations for different levels of geomagnetic activity and for different angular position of radio sources as well.     

Dayside ionospheric uplift during strong geomagnetic storms as detected by the CHAMP,SAC-C,TOPEX and Jason-1 satellites

Ionosphere response to severe geomagnetic storms that occurred in 2001–2003 was analyzed using data of global ionosphere maps (GIM), altimeter data from the Jason-1 and TOPEX satellites, and data of GPS receivers on-board CHAMP and SAC-C satellites. This allowed us to study in detail ionosphere redistribution due to geomagnetic storms, dayside ionospheric uplift and overall dayside TEC increase. It is shown that after the interplanetary magnetic field turns southward and intensifies, the crests of the equatorial ionization anomaly (EIA) travel poleward and the TEC value within the EIA area increases significantly (up to ∼50%). GPS data from the SAC-C satellite show that during the main phase of geomagnetic storms TEC values above the altitude of 715 km are 2–3 times higher than during undisturbed conditions. These effects of dayside ionospheric uplift occur owing to the “super-fountain effect” and last few hours while the enhanced interplanetary electric field impinged on the magnetopause.