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附加IRI模型约束的全球电离层建模及定位精度分析 被引量:3
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作者 杨玲 周春元 +1 位作者 苏小宁 李博峰 《同济大学学报(自然科学版)》 EI CAS CSCD 北大核心 2021年第11期1606-1613,共8页
采用载波相位平滑伪距的全球电离层建模方法,确定了添加国际参考电离层(IRI)模型约束和不同数据选取策略的有效性和必要性。实验分析表明,采用P_(1)、P_(2)原始双频观测数据并添加IRI模型约束后,部分历元电离层建模的整体效果得到了显... 采用载波相位平滑伪距的全球电离层建模方法,确定了添加国际参考电离层(IRI)模型约束和不同数据选取策略的有效性和必要性。实验分析表明,采用P_(1)、P_(2)原始双频观测数据并添加IRI模型约束后,部分历元电离层建模的整体效果得到了显著提高,在观测数据不足的区域内定位误差在北、东、高方向上分别减小了0.260 m、0.146 m和0.103 m,验证了该方法的有效性;将C_(1)观测值作为低精度数据取代缺失P1观测值后,电离层建模的整体效果进一步提升,但损失了模型精度,在观测数据不足的区域内定位误差在北、东、高方向上分别增加0.524 m、0.111 m和1.549 m,说明了利用P_(1)、P_(2)双频观测数据的必要性。 展开更多
关键词 GNSS(Global Navigation Satellites System) 全球电离层 IRI(international reference ionosphere)模型 球谐函数 定位精度
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Tomographic Study of Ionospheric Effects Associated with a Solar Eclipse 被引量:1
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作者 Wu Xiong-bin, Xu Ji-sheng, Ma Shu-ying, Tian MaoSchool of Electronic Information, Wuhan University, Wuhan 430072, Hubei, China 《Wuhan University Journal of Natural Sciences》 EI CAS 2003年第02A期399-404,共6页
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
关键词 ionosphere solar eclipse TOMOGRAPHY total electron content international reference ionosphere
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Performance evaluation of neural network TEC forecasting models over equatorial low-latitude Indian GNSS station 被引量:1
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作者 G.Sivavaraprasad V.S.Deepika +2 位作者 D.Sreenivasa Rao M.Ravi Kumar M.Sridhar 《Geodesy and Geodynamics》 2020年第3期192-201,共10页
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
关键词 Global Positioning System(GPS) Global navigation satellite systems(GNSS) Total electron content(TEC) international reference ionosphere(IRI) Neural networks
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