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
This paper studies the ionospheric effects associated with the solar eclipse of October 24th, 1995 by means of Computerized Ionospheric Tomography (CIT). Since the reconstructed profiles from experimental CIT are spor...This paper studies the ionospheric effects associated with the solar eclipse of October 24th, 1995 by means of Computerized Ionospheric Tomography (CIT). Since the reconstructed profiles from experimental CIT are sporadically located in time, a time domain interpolation method based on Singular Value Decomposition (SVD) technique is proposed and applied to extract the ionospheric effects. The effects can be extracted by comparison analysis between the interpolated CIT profiles of the eclipse days and that of the reference day that are time-aligned. A series of figs have been obtained showing the attenuation of photonization effect at low altitudes and the weakening of plasma’s transportation process at high altitudes, etc. The photonization effect recovered to normal level soon after the last contact. The maximum electron density diminishing is observed about 2 h after the eclipse maximum and the effects seem vanished in the hours followed. Analysis on vertical TEC’s latitudinal-temporal variation gives similar conclusions.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%.
基金the National Natural Science Foundation of China(49984001)
文摘This paper studies the ionospheric effects associated with the solar eclipse of October 24th, 1995 by means of Computerized Ionospheric Tomography (CIT). Since the reconstructed profiles from experimental CIT are sporadically located in time, a time domain interpolation method based on Singular Value Decomposition (SVD) technique is proposed and applied to extract the ionospheric effects. The effects can be extracted by comparison analysis between the interpolated CIT profiles of the eclipse days and that of the reference day that are time-aligned. A series of figs have been obtained showing the attenuation of photonization effect at low altitudes and the weakening of plasma’s transportation process at high altitudes, etc. The photonization effect recovered to normal level soon after the last contact. The maximum electron density diminishing is observed about 2 h after the eclipse maximum and the effects seem vanished in the hours followed. Analysis on vertical TEC’s latitudinal-temporal variation gives similar conclusions.
