A neural network-based ionospheric model for Arecibo

被引：2

作者：

Friedrich, M. ^{[1
]}

Fankhauser, M. ^{[1
]}

Oyeyemi, E. ^{[2
,3
]}

McKinnell, L. A. ^{[2
,3
]}

机构：

[1] Graz Univ Technol, A-8010 Graz, Austria

[2] Hermanus Observ, ZA-7200 Hermanus, South Africa

[3] Rhodes Univ, ZA-6140 Grahamstown, South Africa

来源：

ADVANCES IN SPACE RESEARCH | 2008年 / 42卷 / 04期

关键词：

IRI; Arecibo; neural network; ionosphere;

D O I：

10.1016/j.asr.2007.07.018

中图分类号：

V [航空、航天];

学科分类号：

08 ; 0825 ;

摘要：

The Arecibo Observatory (18 degrees N, 66 degrees W) has the world's largest single dish antenna (300 in diameter). Beyond radio astronomy it can also operate as an incoherent scatter radar and in that mode its figure-of-merit makes it also one of the most powerful world-wide. For the present purpose all electron density data available on the web, from the beginning with the first erratic measurements in 1966 up to 2004 inclusive, were downloaded. The measurements range from about 100 km to beyond 700 km and are essentially evenly distributed, i.e. not dedicated to measure specific geophysical events. From manually edited/inspected data a neural network (NN) was established with season, hour of the day, solar activity and Kp as the input parameters. The performance of this model is checked against a - likewise NN based - global model of foF2, a measure of the maximum electron density of the ionosphere. Considering the diverse data sources and assumptions of the two models it can be concluded that they agree remarkably well. (c) 2008 Published by Elsevier Ltd on behalf of COSPAR.

引用

页码：776 / 781

页数：6

共 11 条

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