首页> 外文会议>CODEC 2012;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模型在赤道电离异常北嵴周围使用多态GPS-TEC

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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:世界上最高的电子含量(TEC)值通常在赤道异常区域发生,导致任何潜在的SBAS系统观察到最大的电离层范围延迟值。 非常高的TEC值的位置和幅度与日期到一天的赤道电气喷射(EEJ)的强度直接相关。 日常变异的异常峰的变化,其强度非常大。 这对常用电离层模型对低纬度地区的适用性施加了严重的局限性。 基于2007至2011年赤道电离异常(EIA)周围的实时低纬度GPS-TEC数据开发了一种模型。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)在赤道地区建立其实用性和适用性,以准确预测。

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