Ionospheric echoes detection in digital ionograms using convolutional neural networks
Date
2019-09-12
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Pontificia Universidad Católica del Perú
Abstract
An ionogram is a graph that shows the distance
that a vertically transmitted wave, of a given frequency, travels
before returning to the earth. The ionogram is shaped by making
a trace of this distance, which is called virtual height, against the
frequency of the transmitted wave. Along with the echoes of the
ionosphere, ionograms usually contain a large amount of noise
of different nature, that must be removed in order to extract
useful information. In the present work, we propose to use a
convolutional neural network model to improve the quality of
the information obtained from digital ionograms, compared to
that using image processing and machine learning techniques, in
the generation of electronic density profiles. A data set of more
than 900,000 ionograms from 5 ionospheric observation stations
is available to use.
Description
Keywords
Redes neuronales (Computación), Ionosfera, Sistemas de transmisión de datos
Citation
Endorsement
Review
Supplemented By
Referenced By
Creative Commons license
Except where otherwised noted, this item's license is described as info:eu-repo/semantics/openAccess