基于地磁坐标和Kriging技术的高纬地区f0F2重构方法

为能够在高纬区域获取高精度电离层参数特性结果,提出了基于地磁坐标的高纬度区域电离层F₂层临界频率（f₀F₂）的重构方法.该方法确定了基于地磁坐标的变异函数,通过求解改进Kriging方程得出估计值.方法的确定取决于对2种坐标系、2类电离层距离计算方法以及尺度因子的选取.通过对俄罗斯6个垂直探测站在太阳活动高年（2013年）和低年（2017年）的f₀F₂历史观测数据使用月中值进行交叉验证,证明了引入地磁坐标和利用球面距离计算方法对高纬度地区进行重构能够达到最优效果.相比现有方法,其整体标准误差和绝对误差均有所降低.上述研究证实了该方法的有效性,对电子信息系统的可用频率预测以及通信效能保障具有重要意义.      

135.6nm夜气辉峰值电子密度反演算法及误差

根据夜间135.6nm大气辉光光强与F₂层峰值电子密度N_mF₂平方成正比的物理机制,在前期夜间135.6nm气辉辐射激发模型研究的基础上建立了峰值电子密度的反演算法,把全球经纬度分成若干格点,每个格点的电离层及中性成分信息分别由IRI2000和MSISE90提供,将电离层及中性成分廓线输入夜气辉辐射激发模型,计算每个格点135.6nm气辉的辐射强度,然后将各个格点的135.6nm气辉辐射强度与电离层廓线输入的N_mF₂平方拟合得到气辉强度与N_mF₂的转换因子.利用此方法可获得不同地方时、季节和太阳活动周期的转换因子组成查算表,进而根据实际探测的135.6nm气辉辐射强度反演相应时空的N_mF₂.最后对该算法的反演误差进行了综合分析,为该算法适用的时空特性提供重要理论支撑.      

基于最大似然估计的远紫外遥感反演电离层电子密度算法

原子氧135.6 nm夜气辉主要由氧离子O+与电子的辐射复合反应生成,一些星载远紫外遥感观测任务证实135.6 nm夜气辉可用于反演电离层电子密度。针对远紫外临边遥感观测反演电离层电子密度,分析了135.6 nm夜气辉辐射强度与电子密度之间的非线型前向模型,基于离散反演理论设计了从夜间135.6 nm临边观测数据反演电子密度高度分布的反演算法,算法应用最大似然估计通过迭代求解电离层参数的最佳拟合值。通过仿真计算了TIMED卫星上全球紫外成像仪GUVI观测的反演结果,验证了本反演算法的可行性。对GUVI的实际观测数据进行反演,获得了电子密度高度分布。通过与GUVI数据的电离层参数对比分析得出,本文建立的反演模型使N_mF₂被高估,同时使h_mF₂被低估。对于不同的太阳活动强度,N_mF₂和 h_mF₂的系统误差分别在10%和5%以内,能较精确地获得电离层参数。精确获得电离层电子密度信息对于提高空间天气预报及电离层模型的修正具有重要意义。      

GNSS电离层模型改正精度评估与分析

电离层时延误差是导航定位信号在空间传播路径上的主要误差源之一,因此全面了解GNSS电离层模型的改正精度具有一定现实意义.根据GPS,BDS和Galileo系统所采用的电离层修正模型,利用2014年电离层校正参数,以高精度全球电离层图为基准,评估分析了三大系统电离层时延的改正精度.结果表明:目前GNSS使用的几种电离层修正模型的改正率在65~75%左右;Galileo系统使用的第二版NeQuick模型与第一版NeQuick模型相比在修正精度上并无显著提高;GPS使用的Klobuchar 8参数模型在北半球25°-45°N的中纬度地区精度很高,但是在全球其他区域精度较低,分布性较差,而NeQuick模型全球改正率分布则较为平均且平滑.      

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NRLMSISE-00模型太阳辐射校正方法

根据空间天气的状态,调整大气模型的相关输入参数能够减小模型的计算误差.通过对比CHAMP卫星在轨大气密度探测数据与NRLMSISE-00模式的计算结果发现,通过调整F_10.7的输入,使轨道大气密度积分的模式计算结果与探测结果之间的误差达到最小,此时的F_10.7被称为理想F_10.7输入（F*）.进一步的分析发现,F*与太阳紫外辐射MgII指数存在很好的相关性,因此可以选择其他的太阳紫外辐射代理参数取代F_10.7,从而减小模型计算误差.本文采用神经网络技术,建立新的太阳紫外辐射代理参量F_euv与MgII,F_10.7等的对应模型,能够根据当日参数值计算F_euv.研究结果表明,新的代理参数能够有效减小NRLMSISE-00的计算误差.      

夜间135.6 nm气辉反演的电离层f0F2与测高仪观测比较研究

在夜间电离层，气辉135.6 nm谱线主要由F层的O⁺和电子的辐射复合过程以及O⁺和O^–的中性复合过程激发，该谱线强度和电离层峰值电子密度Nm F₂存在很强的相关性。利用夜气辉135.6 nm辐射强度与F₂层峰值电子密度Nm F₂的平方成正比的物理模型，建立了在不同经纬度、地方时、季节和太阳活动下均适用的反演算法。通过DMSP卫星上搭载的紫外光谱成像仪(SSUSI)实际观测的135.6 nm气辉辐射强度来反演相应时空的电离层F₂层临界频率f₀F₂，并将其与地基测高仪探测结果做了综合对比。结果表明，在太阳活动高年(2013年)，相对误差小于等于20%的数据占比93.0%，平均相对误差约为7.08%；在太阳活动低年(2017年)，相对误差小于等于20%的数据占比80.8%，平均相对误差约为12.64%。最后，对该算法在太阳活动高低年的反演精度差异进行了分析。     

基于CIT技术的广域增强系统电离层延迟修正算法

提出了一种基于电离层层析成像(CIT)技术的广域增强系统(WAAS)电离层延迟 修正算法. 该算法利用模式基函数与截断奇异值分解正则化组合的方式, 实现WAAS单频用户的电离层延迟误差修正. 基于中国区域23个广域基准站 和10个用户站的仿真结果分析表明, 传统的网格算法和基于CIT技术的电离 层延迟修正算法的电离层延迟修正精度与太阳活动、昼夜变化及地磁纬度 之间均存在明显的相关性. 基于CIT技术的电离层延迟修正算法精度优于网格算法, CIT算法的平均误差与标准差相比网格算法均有较大幅度的下降.      

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.      

基于斜向探测最高可用频率反演电离层参数

提出了一种利用斜向探测F₂层最高可用频率及其对应时延反演传播路径中点临界频率f₀F₂和3000km传输因子M（3000）F₂的新方法.该方法从工程实用角度出发,利用射线传播理论直接反演得到临界频率和3000km传输因子.通过对长春-径阳和新乡-赤峰两条斜向探测链路中点电离层参数的反演分析,验证了方法的稳定性;利用反演结果与北京垂直探测数据对比,验证了方法的准确性;通过与Smith方法的对比,验证了方法的实用性.统计分析显示,此方法具有与Smith方法可比的精度,明显优于参考电离层模型给出的结果,其均方误差为0.48MHz,相对误差为10.50%;具有较好的稳定性,对不同距离的探测链路有较好的适应性,反演精度差异为0.03MHz;具有可操作性强,易于实现的特点.本研究成果可用于短波通信频率实时预报、动态频率管理及其相关领域.      

一种电离层场向不规则体各向异性散射模型

电离层场向不规则体散射具有很强的方向性, 利用电离层场向不规则体散 射进行VHF频段超视距通信时, 需要准确可靠地确定其散射分布特性及路径损 耗等参数. 基于电离层不规则体场向散射的特点, 以地球地磁场为坐标系统, 提出了一种电离层场向不规则体各向异性散射模型, 该模型能够计算前向和后 向散射链路的路径损耗分布、时延展宽和相干带宽等参数, 同时运用该模型对 雷达横向截面的计算结果与已有文献的数据结果进行对比, 证明了该模型的准确性. 该模型能够计算电离层场向不规则体VHF频段的散射分布及路径损耗等参数, 为VHF散射通信链路的设计、布站提供依据和技术指导.      

Evaluation of COMPASS ionospheric model in GNSS positioning

As important products of GNSS navigation message, ionospheric delay model parameters are broadcasted for single-frequency users to improve their positioning accuracy. GPS provides daily Klobuchar ionospheric model parameters based on geomagnetic reference frame, while the regional satellite navigation system of China’s COMPASS broadcasts an eight-parameter ionospheric model, COMPASS Ionospheric Model(CIM), which was generated by processing data from continuous monitoring stations, with updating the parameters every 2 h. To evaluate its performance, CIM predictions are compared to ionospheric delay measurements, along with GPS positioning accuracy comparisons. Real observed data analysis indicates that CIM provides higher correction precision in middle-latitude regions, but relatively lower correction precision for low-latitude regions where the ionosphere has much higher variability. CIM errors for some users show a common bias for in-coming COMPASS signals from different satellites, and hence ionospheric model errors are somehow translated into the receivers’ clock error estimation. In addition, the CIM from the China regional monitoring network are further evaluated for global ionospheric corrections. Results show that in the Northern Hemisphere areas including Asia, Europe and North America, the three-dimensional positioning accuracy using the CIM for ionospheric delay corrections is improved by 7.8%–35.3% when compared to GPS single-frequency positioning ionospheric delay corrections using the Klobuchar model. However, the positioning accuracy in the Southern Hemisphere is degraded due apparently to the lack of monitoring stations there.     

Ionosphere modelling for Galileo single frequency users: Illustration of the combination of the NeQuick model and GNSS data ingestion

The ionospheric effect remains one of the main factors limiting the accuracy of Global Navigation Satellite Systems (GNSS) including Galileo. For single frequency users, this contribution to the error budget will be mitigated by an algorithm based on the NeQuick global ionospheric model. This quick-run empirical model provides flexible solutions for combining ionospheric information obtained from various sources, from GNSS to ionosondes and topside sounders. Hence it constitutes an interesting simulation tool not only serving Galileo needs for mitigation of the ionospheric effect but also widening the use of new data.     

Eccentric dipole approximation of the geomagnetic field: Application to cosmic ray computations

A comparison of the full IGRF model of the geomagnetic field with two simplified models, the truncated IGRF and the eccentric dipole model, is performed. The simplified models were found to provide a reasonable approximation for the large scale geomagnetic field distribution. In the application of the simplified geomagnetic models to the shielding of cosmic rays in the magnetosphere as quantified via the geomagnetic cut-off rigidity, the eccentric dipole and the truncated IGRF provide a good large scale view. The use of the simplified model does not introduce any additional systematic errors at the global scale but may be a source of moderate uncertainty at the regional scale in the tropical Atlantic region. This study quantitatively validates the use of such simplified geomagnetic models when describing the shielding of cosmic rays in the magnetosphere.     

Tightly combined GPS/Galileo RTK for short and long baselines: Model and performance analysis

To ensure the compatibility and interoperability with modernized GPS, Galileo satellites are capable of broadcasting navigation signals on carrier phase frequencies that overlap with GPS, i.e., GPS/Galileo L1-E1/L5-E5a. Moreover, the GPS/Galileo L2-E5b signals have different frequencies with wavelength differences smaller than 4.2?mm. Such overlapping and narrowly spaced signals between GPS and Galileo bring the opportunity to use the tightly combined double-differenced (DD) model for precise real-time kinematic (RTK) positioning, resulting in improved performance of ambiguity resolution and positioning with respect to the classical standard or loosely combined DD model. In this paper, we focus on the model and performance assessment of tightly combined GPS/Galileo L1-E1/L2-E5b/L5-E5a RTK for short and long baselines. We first investigate the tightly combined GPS/Galileo DD observational model for both short and long baselines with simultaneously considering the GPS/Galileo overlapping and non-overlapping frequencies. Particularly, we introduce a reparameterization approach to solve the rank deficiency that caused by the correlation between the DISB parameters and the DD ionospheric parameters for both overlapping and non-overlapping frequencies. Then we present performance assessment for the tightly combined GPS/Galileo RTK model with real-time estimation of the differential inter-system bias (DISB) parameters for short and long baselines in terms of ratio value, ambiguity dilution of precision (ADOP), ambiguity conditional number, decorrelation number, search count, empirical success rate, time-to-first-fix (TTFF), and positioning accuracy. Results from both static and kinematic experiments demonstrated that compared to the loosely combined model, the tightly combined model can deliver improved performance of ambiguity resolution and precise positioning with different satellite visibility. For the car-driven short baseline experiment with 10° elevation cut-off angle, the tightly combined model can not only significantly increase the ratio value by approximately 27.5% (from 16.0 to 20.4), but also reduce the ambiguity ADOP, the conditional number, and the search count in LAMBDA by approximately 22.2% (from 0.027 to 0.021 cycles), 14.9% (from 199.2 to 169.6), and 25.4% (from 150.1 to 112.0), respectively. Comparable decorrelation number, empirical success rate, and positioning accuracy are also obtained. For the car-driven long baseline experiment, it is also observed that the ambiguity resolution performance in terms of the ratio value, the decorrelation number, the condition number, and the search count are significantly improved by approximately 18.5% (from 2.7 to 3.2), 22.0% (from 0.186 to 0.227), 55.9% (from 937.6 to 413.7), and 10.3% (from 43.8 to 39.3), respectively. Moreover, comparable ADOP, empirical success rate, and positioning accuracy are obtained as well. Additionally, the TTFF can be reduced (from 54.1 to 51.8 epochs with 10° elevation cut-off angle) as well from the results of static experiments.     

Ionospheric response to solar and magnetospheric protons during January 15–22, 2005: EAGLE whole atmosphere model results

We present an analysis of the ionosphere and thermosphere response to Solar Proton Events (SPE) and magnetospheric proton precipitation in January 2005, which was carried out using the model of the entire atmosphere EAGLE. The ionization rates for the considered period were acquired from the AIMOS (Atmospheric Ionization Module Osnabrück) dataset. For numerical experiments, we applied only the proton-induced ionization rates of that period, while all the other model input parameters, including the electron precipitations, corresponded to the quiet conditions. In January 2005, two major solar proton events with different energy spectra and proton fluxes occurred on January 17 and January 20. Since two geomagnetic storms and several sub-storms took place during the considered period, not only solar protons but also less energetic magnetospheric protons contributed to the calculated ionization rates. Despite the relative transparency of the thermosphere for high-energy protons, an ionospheric response to the SPE and proton precipitation from the magnetotail was obtained in numerical experiments. In the ionospheric E layer, the maximum increase in the electron concentration is localized at high latitudes, and at heights of the ionospheric F2 layer, the positive perturbations were formed in the near-equatorial region. An analysis of the model-derived results showed that changes in the ionospheric F2 layer were caused by a change in the neutral composition of the thermosphere. We found that in the recovery phase after both solar proton events and the enhancement of magnetospheric proton precipitations associated with geomagnetic disturbances, the TEC and electron density in the F region and in topside ionosphere/plasmasphere increase at low- and mid-latitudes due to an enhancement of atomic oxygen concentration. Our results demonstrate an important role of magnetospheric protons in the formation of negative F-region ionospheric storms. According to our results, the topside ionosphere/plasmasphere and bottom-side ionosphere can react to solar and magnetospheric protons both with the same sign of disturbances or in different way. The same statement is true for TEC and foF2 disturbances. Different disturbances of foF2 and TEC at high and low latitudes can be explained by topside electron temperature disturbances.     

Ionospheric climate index as a driving parameter for the NeQuick model

Ionospheric delay is one of the significant error sources for global navigation satellite system (GNSS) positioning. GNSSs broadcast the coefficients of the ionospheric model to correct ionospheric delay for single-frequency users. A modified three-dimensional model (NeQuick G) based on the NeQuick climatological model is adopted for Galileo users. The NeQuick G model uses the effective ionization level (Az) instead of the sunspot number as the driving parameter. In this study, we introduce the ionospheric climate index (ICI) as a new driving parameter for the NeQuick model. In comparison, the ICI-driven NeQuick model has a better performance than the Az-driven NeQuick G model at both low and high latitudes. In addition, only one GNSS station at low latitudes is required to calculate the ICI, which would save maintenance costs and improve the efficiency of updating the broadcast coefficients. This model has potential application value for future upgrades of Galileo’s ionospheric broadcast model.     

Modelling of Geomagnetic Storm Effects in the Ionosphere of East Asia

This paper presents simulated results of the ionospheric behavior during few geomagnetic storms,which were occurred in the different seasons. The numerical model for ionosphere-plasmasphere coupling was used to interpret the observed variation of ionosphere structure. Reasons why the positive storms are dominant in the winter whereas the negative ones are dominant in the summer season present the special interest for the mid-latitude ionosphere. A theoretical analysis of the processes controlling the ionospheric response to the geomagnetic storms has showed a good agreement between the simulated results and measurements, as well as the crucial role of the neutral composition variations to fit the calculated and the observed ionospheric parameters.      

Parameterized Regional Ionospheric Model and a comparison of its results with experimental data and IRI representations

We describe a Parameterized Regional Ionospheric Model (PARIM) to calculate the spatial and temporal variations of the ionospheric electron density/plasma frequency over the Brazilian sector. The ionospheric plasma frequency values as calculated from an enhanced Sheffield University Plasmasphere–Ionosphere Model (SUPIM) were used to construct the model. PARIM is a time-independent 3D regional model (altitude, longitude/local time, latitude) used to reproduce SUPIM plasma frequencies for geomagnetic quiet condition, for any day of the year and for low to moderately high solar activity. The procedure to obtain the modeled representation uses finite Fourier series so that all plasma frequency dependencies can be represented by Fourier coefficients. PARIM presents very good results, except for the F region peak height (hmF2) near the geomagnetic equator during times of occurrence of the F₃ layer. The plasma frequency calculated by IRI from E region to bottomside of the F region present latitudinal discontinuities during morning and evening times for both solar minimum and solar maximum conditions. Both the results of PARIM and the IRI for the E region peak density show excellent agreement with the observational values obtained during the conjugate point equatorial experiment (COPEX) campaign. The IRI representations significantly underestimate the foF2 and hmF2 compared to the observational results over the COPEX sites, mainly during the evening–nighttime period.