This research investigates the capability of artificial neural networks to predict vertical total electron content(VTEC)over central Anatolia in Turkey.The VTEC dataset was derived from the 19 permanent Global Positio...This research investigates the capability of artificial neural networks to predict vertical total electron content(VTEC)over central Anatolia in Turkey.The VTEC dataset was derived from the 19 permanent Global Positioning System(GPS)stations belonging to the Turkish National Permanent GPS NetworkActive(TUSAGA-Aktif)and International Global Navigation Satellite System Service(IGS)networks.The study area is located at 32.6°E-37.5°E and 36.0°N-42.0°N.Considering the factors inducing VTEC variations in the ionosphere,an artificial neural network(NN)with seven input neurons in a multi-layer perceptron model is proposed.The KURU and ANMU GPS stations from the TUSAGA-Aktif network are selected to implement the proposed neural network model.Based on the root mean square error(RMSE)results from 50 simulation tests,the hidden layer in the NN model is designed with 41 neurons since the lowest RMSE is achieved in this attempt.According to the correlation coefficients,absolute and relative errors,the NN VTEC provides better predictions for hourly and quarterly GPS VTEC.In addition,this paper demonstrates that the NN VTEC model shows better performance than the global IRI2016 model.Regarding the spatial contribution of the GPS network to TEC prediction,the KURU station performs better than ANMU station in fitting with the proposed NN model in the station-based comparison.展开更多
探索了一种新的基准站上空垂直电离层电子浓度(vertical total electron content,VTEC)计算方法,即从单历元整周模糊度和双频观测值入手计算VTEC。结果表明:用此方法计算得到的VTEC与IGS(International GNSS Service)提供的VTEC随时间...探索了一种新的基准站上空垂直电离层电子浓度(vertical total electron content,VTEC)计算方法,即从单历元整周模糊度和双频观测值入手计算VTEC。结果表明:用此方法计算得到的VTEC与IGS(International GNSS Service)提供的VTEC随时间变化趋势一致,且内符合精度良好,能反映电离层活动随时间和纬度的变化规律。展开更多
随着空间目标活动和卫星导航系统的增多,观测电离层数据的途径越来越多,探测精度也越来越高.在Kalman滤波的基础上,利用2016年的国际参考电离层(IRI-2016)模型中电离层垂直电子含量(Vertical Total Electron Content, VTEC),结合地基反...随着空间目标活动和卫星导航系统的增多,观测电离层数据的途径越来越多,探测精度也越来越高.在Kalman滤波的基础上,利用2016年的国际参考电离层(IRI-2016)模型中电离层垂直电子含量(Vertical Total Electron Content, VTEC),结合地基反演得到的VTEC值,利用数据融合算法提高电离层VTEC的近实时反演精度.针对加拿大附近高纬度区域(130°W–150°W, 60°N–70°N)、朝鲜、韩国和日本周边中纬度区域(115°E–135°E, 32.5°N–42.5°N)、洪都拉斯和危地马拉附近低纬度区域(80°W–100°W, 10°N–20°N)进行了观测,比较发现地基反演和数据融合技术得到的电离层VTEC精度都比较高,但是数据融合得到的电离层VTEC在3个区域的精度都明显更好.该算法能够很好地应用在地面基准站数量较多的区域,同时也能应用在地面基准站数量较少或者海洋、沙漠等布设地面基准站不方便的区域,提高电离层VTEC的精度.展开更多
利用下载的JPL-GIM（Jet Propulsion Laboratory—Global Ionosphere Map，美国加利福尼亚喷气动力实验室全球电离层地图）数据，分析了昆明地区2001-2012年VTEC（Vertical Total Electron Content）随时间变化的特性。结果表明，春、...利用下载的JPL-GIM（Jet Propulsion Laboratory—Global Ionosphere Map，美国加利福尼亚喷气动力实验室全球电离层地图）数据，分析了昆明地区2001-2012年VTEC（Vertical Total Electron Content）随时间变化的特性。结果表明，春、秋、冬三季的VTEC平均最高值均出现在“08：00UT”，而夏季的VTEC平均最高值出现在“10：00UT”，四季的VTEC平均最低值出现在“22：00UT”；VTEC变化存在季节异常，即春、秋季节高，夏、冬季节低；昆明地区的VTEC在2001-2009年呈现出逐渐下降的变化趋势，白2010年开始逐渐增强，年际变化与太阳活动及地磁活动变化的趋势呈现出较好的对应关系，且VTEC变化与太阳活动存在较强的相关性，其相关系数达到了0．8以上，而与地磁活动则显示出了相对较弱的相关性。展开更多
文摘This research investigates the capability of artificial neural networks to predict vertical total electron content(VTEC)over central Anatolia in Turkey.The VTEC dataset was derived from the 19 permanent Global Positioning System(GPS)stations belonging to the Turkish National Permanent GPS NetworkActive(TUSAGA-Aktif)and International Global Navigation Satellite System Service(IGS)networks.The study area is located at 32.6°E-37.5°E and 36.0°N-42.0°N.Considering the factors inducing VTEC variations in the ionosphere,an artificial neural network(NN)with seven input neurons in a multi-layer perceptron model is proposed.The KURU and ANMU GPS stations from the TUSAGA-Aktif network are selected to implement the proposed neural network model.Based on the root mean square error(RMSE)results from 50 simulation tests,the hidden layer in the NN model is designed with 41 neurons since the lowest RMSE is achieved in this attempt.According to the correlation coefficients,absolute and relative errors,the NN VTEC provides better predictions for hourly and quarterly GPS VTEC.In addition,this paper demonstrates that the NN VTEC model shows better performance than the global IRI2016 model.Regarding the spatial contribution of the GPS network to TEC prediction,the KURU station performs better than ANMU station in fitting with the proposed NN model in the station-based comparison.
基金supported by the Director Foundation of the Institute of Seismology, Chinese Earthquake Administration (grant No. IS200916012)Nation Key Technology R&D Program (grant No. 2008BAC35B02)National High Technology Research and Development Program of China (grant No. 2007AA12Z169)
文摘探索了一种新的基准站上空垂直电离层电子浓度(vertical total electron content,VTEC)计算方法,即从单历元整周模糊度和双频观测值入手计算VTEC。结果表明:用此方法计算得到的VTEC与IGS(International GNSS Service)提供的VTEC随时间变化趋势一致,且内符合精度良好,能反映电离层活动随时间和纬度的变化规律。
文摘随着空间目标活动和卫星导航系统的增多,观测电离层数据的途径越来越多,探测精度也越来越高.在Kalman滤波的基础上,利用2016年的国际参考电离层(IRI-2016)模型中电离层垂直电子含量(Vertical Total Electron Content, VTEC),结合地基反演得到的VTEC值,利用数据融合算法提高电离层VTEC的近实时反演精度.针对加拿大附近高纬度区域(130°W–150°W, 60°N–70°N)、朝鲜、韩国和日本周边中纬度区域(115°E–135°E, 32.5°N–42.5°N)、洪都拉斯和危地马拉附近低纬度区域(80°W–100°W, 10°N–20°N)进行了观测,比较发现地基反演和数据融合技术得到的电离层VTEC精度都比较高,但是数据融合得到的电离层VTEC在3个区域的精度都明显更好.该算法能够很好地应用在地面基准站数量较多的区域,同时也能应用在地面基准站数量较少或者海洋、沙漠等布设地面基准站不方便的区域,提高电离层VTEC的精度.
文摘利用下载的JPL-GIM（Jet Propulsion Laboratory—Global Ionosphere Map，美国加利福尼亚喷气动力实验室全球电离层地图）数据，分析了昆明地区2001-2012年VTEC（Vertical Total Electron Content）随时间变化的特性。结果表明，春、秋、冬三季的VTEC平均最高值均出现在“08：00UT”，而夏季的VTEC平均最高值出现在“10：00UT”，四季的VTEC平均最低值出现在“22：00UT”；VTEC变化存在季节异常，即春、秋季节高，夏、冬季节低；昆明地区的VTEC在2001-2009年呈现出逐渐下降的变化趋势，白2010年开始逐渐增强，年际变化与太阳活动及地磁活动变化的趋势呈现出较好的对应关系，且VTEC变化与太阳活动存在较强的相关性，其相关系数达到了0．8以上，而与地磁活动则显示出了相对较弱的相关性。
