Tomographic reconstruction of the ionospheric electron density as a function of space and time

Electron density distribution is the major determining parameter of the ionosphere. Computerized Ionospheric Tomography (CIT) is a method to reconstruct ionospheric electron density image by computing Total Electron Content (TEC) values from the recorded Global Positioning Satellite System (GPS) signals. Due to the multi-scale variability of the ionosphere and inherent biases and errors in the computation of TEC, CIT constitutes an underdetermined ill-posed inverse problem. In this study, a novel Singular Value Decomposition (SVD) based CIT reconstruction technique is proposed for the imaging of electron density in both space (latitude, longitude, altitude) and time. The underlying model is obtained from International Reference Ionosphere (IRI) and the necessary measurements are obtained from earth based and satellite based GPS recordings. Based on the IRI-2007 model, a basis is formed by SVD for the required location and the time of interest. Selecting the first few basis vectors corresponding to the most significant singular values, the 3-D CIT is formulated as a weighted least squares estimation problem of the basis coefficients. By providing significant regularization to the tomographic inversion problem with limited projections, the proposed technique provides robust and reliable 3-D reconstructions of ionospheric electron density.     

Evaluation of the IRI-2016 and NeQuick electron content specification by COSMIC GPS radio occultation,ground-based GPS and Jason-2 joint altimeter/GPS observations

We examined performance of two empirical profile-based ionospheric models, namely IRI-2016 and NeQuick-2, in electron content (EC) and total electron content (TEC) representation for different seasons and levels of solar activity. We derived and analyzed EC estimates in several representative altitudinal intervals for the ionosphere and the plasmasphere from the COSMIC GPS radio occultation, ground-based GPS and Jason-2 joint altimeter/GPS observations. It allows us to estimate a quantitative impact of the ionospheric electron density profiles formulation in several altitudinal intervals and to examine the source of the model-data discrepancies of the EC specification from the bottom-side ionosphere towards the GPS orbit altitudes. The most pronounced model-data differences were found at the low latitude region as related to the equatorial ionization anomaly appearance. Both the IRI-2016 and NeQuick-2 models tend to overestimate the daytime ionospheric EC and TEC at low latitudes during all seasons of low solar activity. On the contrary, during high solar activity the model results underestimated the EC/TEC observations at low latitudes. We found that both models underestimated the EC for the topside ionosphere and plasmasphere regions for all levels of solar activity. For low solar activity, the underestimated EC from the topside ionosphere and plasmasphere can compensate the overestimation of the ionospheric EC and, consequently, can slightly decrease the resulted model overestimation of the ground-based TEC. For high solar activity, the underestimated EC from the topside ionosphere and plasmasphere leads to a strengthening of the model underestimation of the ground-based TEC values. We demonstrated that the major source of the model-data discrepancies in the EC/TEC domain comes from the topside ionosphere/plasmasphere system.     

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.      

Regional VTEC modeling with multivariate adaptive regression splines

Different algorithms have been proposed for the modeling of the ionosphere. The most frequently used method is based on the spherical harmonic functions achieving successful results for global modeling but not for the local and regional applications due to the bounded spherical harmonic representation. Irregular data distribution and data gaps cause also difficulties in the global modeling of the ionosphere. In this paper we propose an efficient algorithm with Multivariate Adaptive Regression Splines (MARS) to represent a new non-parametric approach for regional spatio-temporal mapping of the ionospheric electron density using ground-based GPS observations. MARS can handle very large data sets of observations and is an adaptive and flexible method, which can be applied to both linear and non-linear problems. The basis functions are directly obtained from the observations and have space partitioning property resulting in an adaptive model. This property helps to avoid numerical problems and computational inefficiency caused by the number of coefficients, which has to be increased to detect the local variations of the ionosphere. Since the fitting procedure is additive it does not require gridding and is able to process large amounts of data with large gaps. Additionally the model complexity can be controlled by the user via limiting the maximal number of coefficients and the order of products of the basis functions. In this study the MARS algorithm is applied to real data sets over Europe for regional ionosphere modeling. The results are compared with the results of Bernese GPS Software over the same region.     

国际参考电离层IRI－90与中国实测电离层月平均电子密度剖面形状的比较

将太阳活动峰年期间中国4个电离层站垂直探测得到的月平均电子浓度剖面与国际参考电离层IKI-90进行了系统的比较。结果表明国际参考电离层所计算的峰下电子含量(或峰下半厚)总体来说偏大。一天中白天符合较好,晚上较差,对中纬台站较好,对低纬台站较差。      

A realistic simulation framework to evaluate ionospheric tomography

Observation of the 3-dimensional (3-D) electron density of the ionosphere is useful to study large-scale physical processes in space weather events. Ionospheric data assimilation and ionospheric tomography are methods that can create an image of the 3-D electron density distribution. While multiple techniques have been developed over the past 30 years, there are relatively few studies that show the accuracy of the algorithms. This paper outlines a novel simulation approach to test the quality of an ionospheric tomographic inversion. The approach uses observations from incoherent scatter radar (ISR) scans and extrapolates them spatially to create a realistic ionospheric representation. A set of total electron content (TEC) measurements can then be simulated using real geometries from satellites and ground receivers. This data set, for which the ‘truth’ ionosphere is known, is used as input for a tomographic inversion algorithm to estimate the spatial distribution of electron density. The reconstructed ionospheric maps are compared with the truth ionosphere to calculate the difference between the images and the truth.To demonstrate the effectiveness of this simulation framework, an inversion algorithm called MIDAS (Multi-Instrument Data Analysis Software) is evaluated for three geographic regions with differing receiver networks. The results show the importance of the distribution and density of GPS receivers and the use of a realistic prior conditioning of the vertical electron density profile. This paper demonstrates that when these requirements are met, MIDAS can reliably estimate the ionospheric electron density. When the region under study is well covered by GPS receivers, as in mainland Europe or North America, the errors in vertical total electron content (vTEC) are smaller than 1 TECu (2–4%) . In regions with fewer and more sparsely distributed receivers, the errors can be as high as 20–40%. This is caused by poor data coverage and poor spatial resolution of the reconstruction, which has an important effect on the calibration process of the algorithm.     

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.     

Comparison of peak characteristics of F2 ionospheric layer over Tehran region at a low solar activity period with IRI-2001 and IRI-2007 models predictions

In the present work values of peak electron density (NmF2) and height of F2 ionospheric layer (hmF2) over Tehran region at a low solar activity period are compared with the predictions of the International Reference Ionosphere models (IRI-2001 and IRI-2007). Data measured by a digital ionosonde at the ionospheric station of the Institute of Geophysics, University of Tehran from July 2006 to June 2007 are used to perform the calculations. Formulations proposed by  and  are utilized to calculate the hmF2. The International Union of Radio Science (URSI) and International Radio Consultative Committee (CCIR) options are employed to run the IRI-2001 and IRI-2007 models. Results show that both IRI-2007 and IRI-2001 can successfully predict the NmF2 and hmF2 over Tehran region. In addition, the study shows that predictions of IRI-2007 model with CCIR coefficient has closer values to the observations. Furthermore, it is found that the monthly average of the percentage deviation between the IRI models predictions and the values of hmF2 and NmF2 parameters are less than 10% and 21%, respectively.     

地磁暴期间中国中低纬电离层的CIT研究

利用电离层层析成像技术(Computerized Ionospheric Tomography, CIT)处理115°E子午圈附近6个台站的GPS观测数据, 分析了2004年11月地磁暴期间中国中低纬电离层的响应情况. 结果表明, 电离层呈正相扰动, 且不同高度上的响应不同, 800 km以下电子密度有不同程度的增加, 且在峰值高度附近增幅最大, 800 km以上地磁暴的影响并不显著; 伴随地磁能量的注入, 赤道异常峰极向扩展; 随磁扰强度的降低, 电子密度也逐渐恢复至平静水平. 这些结果与以往的理论和观测结果一致, 初步估计扰动是由热层暴环流引起的, 并受到赤道异常峰移动的影响.      

The variability and predictability of the IRI B0, B1 parameters over Grahamstown,South Africa

The International Reference Ionosphere (IRI) parameters B₀ and B₁ provide a representation of the thickness and shape, respectively, of the F2 layer of the bottomside ionosphere. These parameters can be derived from electron density profiles that are determined from vertical incidence ionograms. This paper aims to illustrate the variability of these parameters for a single mid latitude station and demonstrate the ability of the Neural Network (NN) modeling technique for developing a predictive model for these parameters. Grahamstown, South Africa (33.3°S, 26.5°E) was chosen as the mid latitude station used in this study and the B₀ and B₁ parameters for an 11 year period were determined from electron density profiles recorded at that station with a University of Massachusetts Lowell Center for Atmospheric Research (UMLCAR) Digisonde. A preliminary single station NN model was then developed using the Grahamstown data from 1996 to 2005 as a training database, and input parameters known to affect the behaviour of the F2 layer, such as day number, hour, solar and magnetic indices. An analysis of the diurnal, seasonal and solar variations of these parameters was undertaken for the years 2000, 2005 and 2006 using hourly monthly median values. Comparisons between the values derived from measured data and those predicted using the two available IRI-2001 methods (IRI tables and Gulyaeva, T. Progress in ionospheric informatics based on electron density profile analysis of ionograms. Adv. Space Res. 7(6), 39–48, 1987.) and the newly developed NN model are also shown in this paper. The preliminary NN model showed that it is feasible to use the NN technique to develop a prediction tool for the IRI thickness and shape parameters and first results from this model reveal that for the mid latitude location used in this study the NN model provides a more accurate prediction than the current IRI model options.     

Wavelet modelling in support of IRI

The slant total electron content (STEC) of the ionosphere is defined as the integral of the electron density along the ray-path of the signal between the transmitter and the receiver. So-called geometry free GPS measurements provide information on the electron density, which is basically a four-dimensional function depending on spatial position and time. Since ground-based measurements are not very sensitive to the vertical structure within the atmosphere, the ionosphere is often represented by a spherical layer, where all electrons are concentrated. Then the STEC is transformed into the vertical total electron content (VTEC), which is a three-dimensional function depending on longitude, latitude and time.In our approach, we decompose an ionospheric function, i.e. the electron density or the VTEC, into a reference part computed from a given model like the International Reference Ionosphere (IRI) and an unknown correction term expanded in a multi-dimensional series in terms of localizing base functions. The corresponding series coefficients are calculable from GPS measurements applying parameter estimation procedures. Since the GPS receivers are located rather unbalanced, finer structures are modelable just in regions with a sufficient number of observation sites. Due to the localizing feature of B-spline functions we apply a tensor product spline expansion to model the correction term regionally. Furthermore, the multi-resolution representation derived from wavelet analysis allows monitoring the ionosphere at different resolutions levels. We demonstrate the advantages of this procedure by representing a simulated VTEC data set over South America.     

TEC variability near northern EIA crest and comparison with IRI model

Monthly median values of hourly total electron content (TEC) is obtained with GPS at a station near northern anomaly crest, Rajkot (geog. 22.29°N, 70.74°E; geomag. 14.21°N, 144.9°E) to study the variability of low latitude ionospheric behavior during low solar activity period (April 2005 to March 2006). The TEC exhibit characteristic features like day-to-day variability, semiannual anomaly and noon bite out. The observed TEC is compared with latest International Reference Ionosphere (IRI) – 2007 model using options of topside electron density, NeQuick, IRI01-corr and IRI-2001 by using both URSI and CCIR coefficients. A good agreement of observed and predicted TEC is found during the daytime with underestimation at other times. The predicted TEC by NeQuick and IRI01-corr is closer to the observed TEC during the daytime whereas during nighttime and morning hours, IRI-2001 shows lesser discrepancy in all seasons by both URSI and CCIR coefficients.     

Solar activity variations of ionosonde measurements and modeling results

The time series of hourly electron density profiles N(h) obtained at several mid-latitude stations in Europe have been used to obtain N(h) profiles on a monthly basis and to extract both the expected bottomside parameters and a proxy of the ionospheric variability as functions of time and height. With these data we present advances on a “Local Model” technique for the parameters B0 and B1, its applicability to other ionospheric stations, to other bottomside ionospheric parameters, and to modeling the time/height variability of the profile. The Local Model (LM) is an empirical model based on the experimental results of the solar activity dependence of the daily and seasonal behavior of the above parameters. The LM improves the IRI-2001 prediction of the B0 and B1 by factor of two at mid-latitudes. Moreover, the LM can be used to simulate other ionospheric parameters and to build mean N(h) profiles and the deviations from them. The modeling of both the average N(h) profiles and their deviations is an useful tool for ionospheric model users who want to know both the expected patterns and their deviations.     

F-region ionospheric parameters observed in the equatorial and low latitude regions during medium solar activity in the Brazilian sector and comparison with the IRI-2007 model results

The ionospheric sounding observations using the Canadian Advanced Digital Ionosondes (CADIs) operational at Palmas (PAL; 10.2°S, 48.2°W; dip latitude 6.6°S; a near-equatorial station), and São José dos Campos (SJC, 23.2°S, 45.9°W; dip latitude 17.6°S; a low-latitude station located under the southern crest of the equatorial ionospheric anomaly), Brazil, are analyzed during the different seasons viz., winter (June and July 2003), spring (September and October 2003), summer (December 2003 and January 2004), and fall (March and April 2004). The period used has medium solar activity (sunspot number between 77.4 and 39.3). The seasonal mean variations (using only geomagnetically quiet days) of the ionospheric parameters foF2 (critical frequency of the F-region), hpF2 (virtual height at 0.834 foF2; considered to be close to hmF2 (peak height of the F-region)), and h’F (minimum virtual height of the F-region) are calculated and compared between PAL and SJC. The prominent differences between PAL and SJC are as follows: h’F variations show strong post-sunset enhancement at PAL during the seasons of spring, summer, and fall; hpF2 variations show pre-sunrise uplifting of the F-layer at both stations during all the seasons and the hpF2 values during the daytime are lower at SJC compared with PAL during all the seasons; the foF2 variations show mid-day bite-out at PAL during all the seasons and SJC shows strong equatorial ionospheric anomaly during summer and fall seasons. Also, the seasonal variations of the ionospheric parameters foF2 and hpF2 (with ±1 standard deviation) observed at PAL and SJC are compared with the IRI-2007 model results of foF2 and hmF2. In addition, variations of the foF2 and hpF2 observed at SJC are compared with the IRI-2001 model results of foF2 and hmF2. It should be pointed out that the ionospheric parameter hpF2 is much easier to obtain using computer program developed at UNIVAP compared with hmF2 (using POLAN program). During the daytime due to underlying ionization hpF2 estimated is higher (approximately 50 km) than the true peak height hmF2. During the nighttime hpF2 is fairly close to hmF2. The comparison between the foF2 variations observed at PAL and SJC with the IRI-2007 model results shows a fairly good agreement during all the seasons. However, the comparison between the hpF2 variations observed at PAL and SJC with the hmF2 variations with the IRI-2007 model results shows: (1) a fairly good agreement during the nighttime in all the seasons; (2) the model results do not show the pre-sunrise uplifting of the F-layer at PAL and SJC in any season; (3) the model results do not show the post-sunset uplifting of the F-layer at PAL; (4) considering that, in general, hpF2 is higher than hmF2 during the daytime by about 50 km, the model results are in good agreement at PAL and SJC during all the seasons except summer at SJC, when large discrepancies in the observed hpF2 and modeled hmF2 are observed. Also, it has been observed that, in general, hmF2 values for SJC calculated using IRI-2001 are higher than IRI-2007 during the daytime in winter, summer, and fall. However, hmF2 values for SJC calculated using IRI-2001, are lower than IRI-2007 during the nighttime in spring.     

Application of neural networks to South African GPS TEC modelling

The propagation of radio signals in the Earth’s atmosphere is dominantly affected by the ionosphere due to its dispersive nature. Global Positioning System (GPS) data provides relevant information that leads to the derivation of total electron content (TEC) which can be considered as the ionosphere’s measure of ionisation. This paper presents part of a feasibility study for the development of a Neural Network (NN) based model for the prediction of South African GPS derived TEC. The South African GPS receiver network is operated and maintained by the Chief Directorate Surveys and Mapping (CDSM) in Cape Town, South Africa. Vertical total electron content (VTEC) was calculated for four GPS receiver stations using the Adjusted Spherical Harmonic (ASHA) model. Factors that influence TEC were then identified and used to derive input parameters for the NN. The well established factors used are seasonal variation, diurnal variation, solar activity and magnetic activity. Comparison of diurnal predicted TEC values from both the NN model and the International Reference Ionosphere (IRI-2001) with GPS TEC revealed that the IRI provides more accurate predictions than the NN model during the spring equinoxes. However, on average the NN model predicts GPS TEC more accurately than the IRI model over the GPS locations considered within South Africa.     

Evaluating the IRI topside model for the South African region: An overview of the modelling techniques

The representation of the topside ionosphere (the region above the F2 peak) is critical because of the limited experimental data available. Over the years, a wide range of models have been developed in an effort to represent the behaviour and the shape of the electron density (Ne) profile of the topside ionosphere. Various studies have been centred around calculating the vertical scale height (VSH) and have included (a) obtaining VSH from Global Positioning System (GPS) derived total electron content (TEC), (b) calculating the VSH from ground-based ionosonde measurements, (c) using topside sounder vertical Ne profiles to obtain the VSH. One or a combination of the topside profilers (Chapman function, exponential function, sech-squared (Epstein) function, and/or parabolic function) is then used to reconstruct the topside Ne profile. The different approaches and the modelling techniques are discussed with a view to identifying the most adequate approach to apply to the South African region’s topside modelling efforts. The IRI-2001 topside model is evaluated based on how well it reproduces measured topside profiles over the South African region. This study is a first step in the process of developing a South African topside ionosphere model.     

Evaluation of the improvement of IRI-2016 over IRI-2012 at the India low-latitude region during the ascending phase of cycle 24

This paper investigated the performance of the latest International Reference Ionosphere model (IRI-2016) over that of IRI-2012 in predicting total electron content (TEC) at three different stations in the Indian region. The data used were Global Positioning System (GPS) data collected during the ascending phase of solar cycle 24 over three low-latitude stations in India namely; Bangalore (13.02°N Geographic latitude, 77.57°E Geographic longitude), Hyderabad (17.25°N Geographic latitude, 78.30°E Geographic longitude) and Surat (21.16°N Geographic latitude, 72.78°E Geographic longitude). Monthly, the seasonal and annual variability of GPS-TEC have been compared with those derived from International Reference Ionosphere IRI-2016 and IRI-2012 with two different options of topside electron density: NeQuick and IRI01-corr. It is observed that both versions of IRI (i.e., IRI-2012 and IRI-2016) predict the GPS-TEC with some deviations, the latest version of IRI (IRI-2016) predicted the TEC similar to those predicted by IRI-2012 for all the seasons at all stations except for morning hours (0500 LT to 1000?LT). This shows that the effect of the updated version is seen only during morning hours and also that there is no change in TEC values by IRI-2016 from those predicted by IRI-2012 for the rest of the time of the day in the Indian low latitude region. The semiannual variations in the daytime maximum values of TEC are clearly observed from both GPS and model-derived TEC values with two peaks around March-April and September-October months of each year. Further, the Correlation of TEC derived by IRI-2016 and IRI-2012 with EUV and F10.7 shows similar results. This shows that the solar input to the IRI-2016 is similar to IRI 2012. There is no significant difference observed in TEC, bottom-side thickness (B0) and shape (B1) parameter predictions by both the versions of the IRI model. However, a clear improvement is visible in hmF2 and NmF2 predictions by IRI-2016 to that by IRI-2012. The SHU-2015 option of the IRI-2016 gives a better prediction of NmF2 for all the months at low latitude station Ahmedabad compare to AMTB 2013.     

The quiet nighttime low-latitude ionosphere as observed by TIMED/GUVI

In this paper, we examine the nighttime ionosphere climatology structure in the low latitude region and discrepancies between Global Ultraviolet Imager (GUVI) observations and the IRI model predictions using (1) the magnetic zonal mean of electron number density as a function of altitude and magnetic latitude, (2) vertical electron density profiles at various levels of F10.7 index, (3) nighttime descent and magnitude decrease of the ionosphere, (4) point-to-point comparisons of F-peak height (hmF2) and density (NmF2), and (5) the magnetic longitudinal variations of hmF2 and NmF2. The data collected from the Thermosphere, Ionosphere, Mesosphere, Energetics, and Dynamics (TIMED) mission since its launch in December 2001 have provided great opportunities for many scientific investigations of the ionosphere. In this analysis, we investigate the climatology of the nighttime low-latitude ionosphere under low geomagnetic activity (kp ? 4) using the electron density profiles inferred from the airglow measurements obtained by the GUVI aboard the TIMED spacecraft and compared with the results obtained from IRI (International Reference Ionosphere) model-2001. The observed climatology is an essential tool for further understanding the electrodynamics in the low-latitude region and improving the model’s prediction capability. The time range of the GUVI data used in this study is from 2002 (day 053) to 2006 (day 304), and the IRI model predictions were produced at every GUVI location. The ionosphere observed is generally of greater density than what IRI predicts throughout the night for all four seasons for low and moderate solar activity while the model over-predicts the electron density near the F-region peak at high solar activity before midnight. Observations show that the height of the F-region peak has a steep descent from dusk to midnight and near midnight the height of layer is insensitive to solar conditions, significantly different than what is predicted by IRI. Longitudinal features shown in GUVI data are present in the low-latitude ionosphere after sunset and continue through to midnight after which the low-latitude ionosphere is largely zonally symmetric.     

The use of ionospheric tomography and elevation masks to reduce the overall error in single-frequency GPS timing applications

Signals from Global Positioning System (GPS) satellites at the horizon or at low elevations are often excluded from a GPS solution because they experience considerable ionospheric delays and multipath effects. Their exclusion can degrade the overall satellite geometry for the calculations, resulting in greater errors; an effect known as the Dilution of Precision (DOP). In contrast, signals from high elevation satellites experience less ionospheric delays and multipath effects. The aim is to find a balance in the choice of elevation mask, to reduce the propagation delays and multipath whilst maintaining good satellite geometry, and to use tomography to correct for the ionosphere and thus improve single-frequency GPS timing accuracy. GPS data, collected from a global network of dual-frequency GPS receivers, have been used to produce four GPS timing solutions, each with a different ionospheric compensation technique. One solution uses a 4D tomographic algorithm, Multi-Instrument Data Analysis System (MIDAS), to compensate for the ionospheric delay. Maps of ionospheric electron density are produced and used to correct the single-frequency pseudorange observations. This method is compared to a dual-frequency solution and two other single-frequency solutions: one does not include any ionospheric compensation and the other uses the broadcast Klobuchar model. Data from the solar maximum year 2002 and October 2003 have been investigated to display results when the ionospheric delays are large and variable. The study focuses on Europe and results are produced for the chosen test site, VILL (Villafranca, Spain). The effects of excluding all of the GPS satellites below various elevation masks, ranging from 5° to 40°, on timing solutions for fixed (static) and mobile (moving) situations are presented. The greatest timing accuracies when using the fixed GPS receiver technique are obtained by using a 40° mask, rather than a 5° mask. The mobile GPS timing solutions are most accurate when satellites at lower elevations continue to be included: using a mask between 10° and 20°. MIDAS offers the most accurate and least variable single-frequency timing solution and accuracies to within 10 ns are achieved for fixed GPS receiver situations. Future improvements are anticipated by combining both GPS and Galileo data towards computing a timing solution.     

国际参考电离层模型输出参数峰值高度性能

电离层峰值高度H_mF₂是描述电离层形态的重要参数之一,国际参考电离层模型IRI-2016中融入了大量电离层测高仪和无线电掩星探测数据,用以提升H_mF₂的预测精度.本文利用太阳活动低年（2007—2010年）气象、电离层和气候卫星联合观测系统COSMIC探测数据描述全球范围内COSMIC H_mF₂的三维形态变化,对比分析了IRI-2016与IRI-2012模型的预测结果,同时分析了IRI-2016模型输出H_mF₂的性能.结果表明,IRI模型在中高纬度地区的输出结果高于COSMIC反演结果,而赤道及低纬地区则大都偏低.与IRI-2012模型相比,IRI-2016模型的输出结果在夜间至凌晨时段呈现较为明显的纬向梯度变化且大部分区域输出值偏高,但在白天时段赤道附近区域的输出值大都偏低.上述结果为电离层IRI模型的完善提供了一定参考.