Global Positioning System(GPS)services could be improved through prediction of ionospheric delays for satellite-based radio signals.With respect to latitude,longitude,local time,season,solar cycle and geomagnetic acti...Global Positioning System(GPS)services could be improved through prediction of ionospheric delays for satellite-based radio signals.With respect to latitude,longitude,local time,season,solar cycle and geomagnetic activity the Total Electron Content(TEC)have significant variations in both time and space.These temporal and spatial TEC variations driven by interplanetary space weather conditions such as solar and geomagnetic activities can degrade the communication and navigation links of GPS.Hence,in this paper,performance of TEC forecasting models based on Neural Networks(NN)have been evaluated to forecast(1-h ahead)ionospheric TEC over equatorial low latitude Bengaluru e12:97+N;77:59+ET,Global Navigation Satellite System(GNSS)station,India.The VTEC data is collected for 2009 e2016(8 years)during current 24 th solar cycle.The input space for the NN models comprise the solar Extreme UV flux,F10.7 proxy,a geomagnetic planetary A index(AP)index,sunspot number(SSN),disturbance storm time(DST)index,solar wind speed(Vsw),solar wind proton density(Np),Interplanetary Magnetic Field(IMF Bz).The performance of NN based TEC forecast models and International Reference Ionosphere,IRI-2016 global TEC model has evaluated during testing period,2016.The NN based model driven by all the inputs,which is a NN unified model(NNunq)has shown better accuracy with Mean Absolute Error(MAE)of 3.15 TECU,Mean Square Deviation(MSD)of 16.8 and Mean Absolute Percentage Error(MAPE)of 19.8%and is 1 e25%more accurate than the other NN based TEC forecast models(NN1,NN2 and NN3)and IRI-2016 model.NNunq model has less Root Mean Square Error(RMSE)value 3.8 TECU and highest goodness-of-fit(R2)with 0.85.The experimental results imply that NNunq/NN1 model forecasts ionospheric TEC accurately across equatorial low-latitude GNSS station and IRI-2016 model performance is necessarily improved as its forecast accuracy is limited to 69 e70%.展开更多
由于电离层电子密度随时间变化,且空间分布不均匀,对不同频段的无线电波产生延缓和折射,因此电离层电子密度变化是影响短波通信、卫星通信、全球导航卫星系统和其他空间通信质量的一个主要因素,本文对全球电离层电子密度(Number of elec...由于电离层电子密度随时间变化,且空间分布不均匀,对不同频段的无线电波产生延缓和折射,因此电离层电子密度变化是影响短波通信、卫星通信、全球导航卫星系统和其他空间通信质量的一个主要因素,本文对全球电离层电子密度(Number of electron,Ne)的预测工作对短波通信设备三维射线实时追踪定位提供必要条件。本文采用国际电离层参考模型提供的2016年电离层Ne数据,根据数据的三维空间时间序列特征,搭建了自编码器和卷积长短期记忆(Convolutional Long Short-Term Memory Network,Conv LSTM)网络组成的网络结构,在不引入地球自转周期之外任何先验知识的条件下,对Ne数据进行深度学习并实现预测,首先通过实验对比了SGD、Adagrad、Adadelta、Adam、Adamax和Nadam六种优化算法的性能,又对比了三种预测策略的均方根误差(Root Mean Square Error, RMSE),1h-to-1h预测策略的全球平均RMSE为1.0 NEU(最大值的0.4%),1h-to-24h和24h-to-24h预测策略的全球平均RMSE为6.3 NEU(2.6%)。由实验结果得出以下结论,一是Nadam优化算法更适合电离层Ne的深度学习,二是1h预测策略的性能与之前类似的电离层TEC预测工作(RMSE高于1.5 TECU,最大值的1%)相比有竞争力,但预测时间太短且对数据的实时性要求较高,三是两种24h预测策略虽能实现长期预测但性能不理想,要实现三维空间时间序列的长期高精度预测需要进一步改善神经网络、模型结构和预测策略。展开更多
The algebraic reconstruction technique(ART),multiplicative algebraic reconstruction technique(MART),and simultaneous iterative reconstruction technique(SIRT)are computational methodologies extensively utilized within ...The algebraic reconstruction technique(ART),multiplicative algebraic reconstruction technique(MART),and simultaneous iterative reconstruction technique(SIRT)are computational methodologies extensively utilized within the field of computerized ionospheric tomography(CIT)to facilitate three-dimensional reconstruction of the ionospheric morphology.However,reconstruction accuracy elicits recurrent disputes over its practical application,and people usually attribute this issue to incomplete and uneven coverage of the measurements.The Thermosphere Ionosphere Electrodynamics General Circulation Model(TIEGCM)offers a reasonable physics-based ionospheric background and is widely utilized in ionospheric research.We use the TIEGCM simulations as the targeted ionosphere because the current measurements are far from able to realistically reproduce the ionosphere in detail.Optimized designations of satellite measurements are conducted to investigate the limiting performance of CIT methods in ionospheric reconstruction.Similar to common practice,electron density distributions from outputs of the International Reference Ionosphere(IRI)model are used as the iterative initial value in CIT applications.The outcomes suggest that despite data coverage,iterative initial conditions also play an essential role in ionospheric reconstruction.In particular,in the longitudinal sectors where the iterative initial height of the F2-layer peak electron density(hmF2)differs substantially from the background densities,none of the three CIT methods can reproduce the exact background profile.When hmF2 is close but the ionospheric F2-layer peak density(NmF2)is different between the targeted background and initial conditions,the MART performs better than the ART and SIRT,as evidenced by the correlation coefficients of MART being above 0.97 and those of ART and SIRT being below 0.85.In summary,this investigation reveals the potential uncertainties in traditional CIT reconstruction,particularly when realistic hmF2 or NmF2 values differ substantially from the initial CIT conditions.展开更多
This study deals with Peak of electron density in F2-layer sensibility scale during quiet time on solar minimum. Peaks of electron density in F2-layer (NmF2) values at the quietest days are compared to those carried o...This study deals with Peak of electron density in F2-layer sensibility scale during quiet time on solar minimum. Peaks of electron density in F2-layer (NmF2) values at the quietest days are compared to those carried out from the two nearest days (previous and following of quietest day). The study uses International Reference Ionosphere (IRI) for ionosphere modeling. The located station is Ouagadougou, in West Africa. Solar minimum of phase 22 is considered in this study. Using three core principles of ionosphere modeling under IRI running conditions, the study enables to carry out Peak of electron density in F2-layer values during the quietest days of the characteristic months for the four different seasons. These parameters are compared to those of the previous and the following of the quietest days (the day before and following each quietest selected day) at the same hour. The knowledge of NmF2 values at the quietest days and at the two nearest days enables to calculate the relative error that can be made on this parameter. This calculation highlights insignificant relative errors. This means that NmF2 values at the two nearest days of each quietest day on solar minimum can be used for simulating the quietest days’ behavior. NmF2 values obtained by running IRI model have good correlation with those carried out by Thermosphere-Ionosphere-Electrodynamics-General Circulation Model (TIEGCM).展开更多
Ionosphere layer is the atmosphere region which reflects radio waves for telecommunication. The density in particles in this layer influences the quality of communication. This study deals with the effects of Total El...Ionosphere layer is the atmosphere region which reflects radio waves for telecommunication. The density in particles in this layer influences the quality of communication. This study deals with the effects of Total Electron Contents (TEC) on the critical frequency of radio waves in the F2-layer. Total Electron Contents parameter symbolizes electron bulk surface density in ionosphere layer. Above critical frequency value in F2 layer (foF2), radio waves pass through ionosphere. The knowledge of this value enables to calibrate transmission frequencies. In this study, we consider TEC effects on foF2 under quiet time conditions during the maximum and the minimum of solar cycle 22, at Ouagadougou station, in West Africa. The study also considers the effects of seasons and the hourly variability of TEC and foF2. This work shows winter anomaly on foF2 and TEC on minimum and maximum of solar cycle phase respectively. Running International Reference Ionosphere (IRI) model enables to carry out the effects of TEC on foF2 by use of their monthly average values. This leads to a new approach to calibrate radio transmitters.展开更多
国际参考电离层模型IRI(the international reference ionosphere model)是利用全球电离层测站以及卫星观测数据建立的电离层经验模型,并广泛用于电离层研究领域.本文选用2014年地磁暴平静期的IRI-2016模式和电离层垂测仪的数据,对电离...国际参考电离层模型IRI(the international reference ionosphere model)是利用全球电离层测站以及卫星观测数据建立的电离层经验模型,并广泛用于电离层研究领域.本文选用2014年地磁暴平静期的IRI-2016模式和电离层垂测仪的数据,对电离层F2层峰值电子密度NmF2和峰值高度HmF2两个物理量,通过IRI模型最新版本(IRI-2016)在地磁环境平静期的误差精度进行评估.根据不同磁倾角范围分别选择5个台站(Juliusruh(54°N,13°E)磁倾角:68.54°,Okinawa(26°N,128°E)磁倾角:37.26°,Jicamarca(12°S,77°W)磁倾角:-0.26°,Port_Stanley(52°S,58°W)磁倾角:-51.20°,Hermanus(34°S,19°E)磁倾角:-64.24°)进行NmF2和HmF2参数对比分析.5个台站中Port_Stanley站的NmF2相关性最差(相关系数0.68),Okinawa站HmF2相关性最差(相关系数0.52),Juliusruh站两个参数的相关性最高(相关系数0.87).以Juliusruh站为例进行白昼、夜晚以及不同季节的分析,可以看出白昼误差明显低于夜晚,相较于分季(春或秋)和冬季,IRI模型在夏季预测效果最好.5个台站的研究结果表明,IRI模型与垂测仪数据具备一致性,IRI模型的值高于实测数据值.展开更多
基金the research project titled"Implementation of Deep Learning Algorithms to Develop Web based Ionospheric Time Delays Forecasting System over Indian Region using Ground based GNSS and NAVigation with Indian Constellation(NAVIC)observations"sponsored by Science&Engineering Research Board(SERB)(A statutory body of the Department of Science&Technology,Government of India,New Delhi,India,vide sanction order No:ECR/2018/001701Department of Science and Technology,New Delhi,India for funding this research through SR/FST/ESI-130/2013(C)FIST program
文摘Global Positioning System(GPS)services could be improved through prediction of ionospheric delays for satellite-based radio signals.With respect to latitude,longitude,local time,season,solar cycle and geomagnetic activity the Total Electron Content(TEC)have significant variations in both time and space.These temporal and spatial TEC variations driven by interplanetary space weather conditions such as solar and geomagnetic activities can degrade the communication and navigation links of GPS.Hence,in this paper,performance of TEC forecasting models based on Neural Networks(NN)have been evaluated to forecast(1-h ahead)ionospheric TEC over equatorial low latitude Bengaluru e12:97+N;77:59+ET,Global Navigation Satellite System(GNSS)station,India.The VTEC data is collected for 2009 e2016(8 years)during current 24 th solar cycle.The input space for the NN models comprise the solar Extreme UV flux,F10.7 proxy,a geomagnetic planetary A index(AP)index,sunspot number(SSN),disturbance storm time(DST)index,solar wind speed(Vsw),solar wind proton density(Np),Interplanetary Magnetic Field(IMF Bz).The performance of NN based TEC forecast models and International Reference Ionosphere,IRI-2016 global TEC model has evaluated during testing period,2016.The NN based model driven by all the inputs,which is a NN unified model(NNunq)has shown better accuracy with Mean Absolute Error(MAE)of 3.15 TECU,Mean Square Deviation(MSD)of 16.8 and Mean Absolute Percentage Error(MAPE)of 19.8%and is 1 e25%more accurate than the other NN based TEC forecast models(NN1,NN2 and NN3)and IRI-2016 model.NNunq model has less Root Mean Square Error(RMSE)value 3.8 TECU and highest goodness-of-fit(R2)with 0.85.The experimental results imply that NNunq/NN1 model forecasts ionospheric TEC accurately across equatorial low-latitude GNSS station and IRI-2016 model performance is necessarily improved as its forecast accuracy is limited to 69 e70%.
文摘由于电离层电子密度随时间变化,且空间分布不均匀,对不同频段的无线电波产生延缓和折射,因此电离层电子密度变化是影响短波通信、卫星通信、全球导航卫星系统和其他空间通信质量的一个主要因素,本文对全球电离层电子密度(Number of electron,Ne)的预测工作对短波通信设备三维射线实时追踪定位提供必要条件。本文采用国际电离层参考模型提供的2016年电离层Ne数据,根据数据的三维空间时间序列特征,搭建了自编码器和卷积长短期记忆(Convolutional Long Short-Term Memory Network,Conv LSTM)网络组成的网络结构,在不引入地球自转周期之外任何先验知识的条件下,对Ne数据进行深度学习并实现预测,首先通过实验对比了SGD、Adagrad、Adadelta、Adam、Adamax和Nadam六种优化算法的性能,又对比了三种预测策略的均方根误差(Root Mean Square Error, RMSE),1h-to-1h预测策略的全球平均RMSE为1.0 NEU(最大值的0.4%),1h-to-24h和24h-to-24h预测策略的全球平均RMSE为6.3 NEU(2.6%)。由实验结果得出以下结论,一是Nadam优化算法更适合电离层Ne的深度学习,二是1h预测策略的性能与之前类似的电离层TEC预测工作(RMSE高于1.5 TECU,最大值的1%)相比有竞争力,但预测时间太短且对数据的实时性要求较高,三是两种24h预测策略虽能实现长期预测但性能不理想,要实现三维空间时间序列的长期高精度预测需要进一步改善神经网络、模型结构和预测策略。
基金supported by the National Key R&D Program of China(Grant No.2022YFF0503702)the National Natural Science Foundation of China(Grant No.42074186)the Key Laboratory of Geospace Environment,Chinese Academy of Sciences,University of Science&Technology of China.
文摘The algebraic reconstruction technique(ART),multiplicative algebraic reconstruction technique(MART),and simultaneous iterative reconstruction technique(SIRT)are computational methodologies extensively utilized within the field of computerized ionospheric tomography(CIT)to facilitate three-dimensional reconstruction of the ionospheric morphology.However,reconstruction accuracy elicits recurrent disputes over its practical application,and people usually attribute this issue to incomplete and uneven coverage of the measurements.The Thermosphere Ionosphere Electrodynamics General Circulation Model(TIEGCM)offers a reasonable physics-based ionospheric background and is widely utilized in ionospheric research.We use the TIEGCM simulations as the targeted ionosphere because the current measurements are far from able to realistically reproduce the ionosphere in detail.Optimized designations of satellite measurements are conducted to investigate the limiting performance of CIT methods in ionospheric reconstruction.Similar to common practice,electron density distributions from outputs of the International Reference Ionosphere(IRI)model are used as the iterative initial value in CIT applications.The outcomes suggest that despite data coverage,iterative initial conditions also play an essential role in ionospheric reconstruction.In particular,in the longitudinal sectors where the iterative initial height of the F2-layer peak electron density(hmF2)differs substantially from the background densities,none of the three CIT methods can reproduce the exact background profile.When hmF2 is close but the ionospheric F2-layer peak density(NmF2)is different between the targeted background and initial conditions,the MART performs better than the ART and SIRT,as evidenced by the correlation coefficients of MART being above 0.97 and those of ART and SIRT being below 0.85.In summary,this investigation reveals the potential uncertainties in traditional CIT reconstruction,particularly when realistic hmF2 or NmF2 values differ substantially from the initial CIT conditions.
文摘This study deals with Peak of electron density in F2-layer sensibility scale during quiet time on solar minimum. Peaks of electron density in F2-layer (NmF2) values at the quietest days are compared to those carried out from the two nearest days (previous and following of quietest day). The study uses International Reference Ionosphere (IRI) for ionosphere modeling. The located station is Ouagadougou, in West Africa. Solar minimum of phase 22 is considered in this study. Using three core principles of ionosphere modeling under IRI running conditions, the study enables to carry out Peak of electron density in F2-layer values during the quietest days of the characteristic months for the four different seasons. These parameters are compared to those of the previous and the following of the quietest days (the day before and following each quietest selected day) at the same hour. The knowledge of NmF2 values at the quietest days and at the two nearest days enables to calculate the relative error that can be made on this parameter. This calculation highlights insignificant relative errors. This means that NmF2 values at the two nearest days of each quietest day on solar minimum can be used for simulating the quietest days’ behavior. NmF2 values obtained by running IRI model have good correlation with those carried out by Thermosphere-Ionosphere-Electrodynamics-General Circulation Model (TIEGCM).
文摘Ionosphere layer is the atmosphere region which reflects radio waves for telecommunication. The density in particles in this layer influences the quality of communication. This study deals with the effects of Total Electron Contents (TEC) on the critical frequency of radio waves in the F2-layer. Total Electron Contents parameter symbolizes electron bulk surface density in ionosphere layer. Above critical frequency value in F2 layer (foF2), radio waves pass through ionosphere. The knowledge of this value enables to calibrate transmission frequencies. In this study, we consider TEC effects on foF2 under quiet time conditions during the maximum and the minimum of solar cycle 22, at Ouagadougou station, in West Africa. The study also considers the effects of seasons and the hourly variability of TEC and foF2. This work shows winter anomaly on foF2 and TEC on minimum and maximum of solar cycle phase respectively. Running International Reference Ionosphere (IRI) model enables to carry out the effects of TEC on foF2 by use of their monthly average values. This leads to a new approach to calibrate radio transmitters.
文摘国际参考电离层模型IRI(the international reference ionosphere model)是利用全球电离层测站以及卫星观测数据建立的电离层经验模型,并广泛用于电离层研究领域.本文选用2014年地磁暴平静期的IRI-2016模式和电离层垂测仪的数据,对电离层F2层峰值电子密度NmF2和峰值高度HmF2两个物理量,通过IRI模型最新版本(IRI-2016)在地磁环境平静期的误差精度进行评估.根据不同磁倾角范围分别选择5个台站(Juliusruh(54°N,13°E)磁倾角:68.54°,Okinawa(26°N,128°E)磁倾角:37.26°,Jicamarca(12°S,77°W)磁倾角:-0.26°,Port_Stanley(52°S,58°W)磁倾角:-51.20°,Hermanus(34°S,19°E)磁倾角:-64.24°)进行NmF2和HmF2参数对比分析.5个台站中Port_Stanley站的NmF2相关性最差(相关系数0.68),Okinawa站HmF2相关性最差(相关系数0.52),Juliusruh站两个参数的相关性最高(相关系数0.87).以Juliusruh站为例进行白昼、夜晚以及不同季节的分析,可以看出白昼误差明显低于夜晚,相较于分季(春或秋)和冬季,IRI模型在夏季预测效果最好.5个台站的研究结果表明,IRI模型与垂测仪数据具备一致性,IRI模型的值高于实测数据值.
