首页> 外文会议>2012 5th International Conference on Computers and Devices for Communication >Neural network based TEC model using multistation GPS-TEC around the northern crest of equatorial ionization anomaly
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Neural network based TEC model using multistation GPS-TEC around the northern crest of equatorial ionization anomaly

机译:基于神经网络的TEC模型,使用多站GPS-TEC围绕赤道电离异常北部波峰

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摘要

The highest Total Electron Content (TEC) values in the world normally occur at Equatorial Anomaly region resulting in largest ionospheric range delay values observed for any potential SBAS system. The location and magnitude of the very high TEC values are directly related to the strength of the Equatorial Electrojet (EEJ) on day to day basis. The day to day variability of the location of the anomaly peak and its intensity is very large. This imposes severe limitations on the applicability of commonly used ionospheric models to the low latitude regions. A model is developed based on real time low latitude GPS-TEC data measured around the northern crest of the Equatorial Ionization Anomaly (EIA) during 2007 through 2011. This model is compared with standard ionospheric models like International Reference Ionosphere (IRI) and Parameterized Ionospheric Model (PIM) to establish its utility and applicability in the equatorial region for accurate predictions.
机译:世界上最高的总电子含量(TEC)值通常发生在赤道异常区域,导致任何潜在的SBAS系统观测到的最大电离层范围延迟值。 TEC值非常高的位置和大小与赤道电喷(EEJ)的日常强度直接相关。异常峰的位置及其强度的日常变化非常大。这严重限制了常用电离层模型在低纬度地区的适用性。基于2007年至2011年在赤道电离异常(EIA)北顶附近测得的实时低纬度GPS-TEC数据,开发了一个模型。将该模型与国际参考电离层(IRI)和参数化电离层等标准电离层模型进行了比较。模型(PIM),以建立其在赤道地区的实用性和适用性,以进行准确的预测。

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