Satellite Orbit Prediction Using Big Data and Soft Computing Techniques to Avoid Space Collisions

The number of satellites and debris in space is dangerously increasing through the years. For that reason, it is mandatory to design techniques to approach the position of a given object at a given time. In this paper, we present a system to do so based on a database of satellite positions according...

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Detalles Bibliográficos
Autores principales: Puente, Cristina, Sáenz Nuño, María, Villa Monte, Augusto, Olivas Varela, José Ángel
Formato: Articulo
Lenguaje:Inglés
Publicado: 2021
Materias:
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/125418
https://www.mdpi.com/2227-7390/9/17/2040
Aporte de:
id I19-R120-10915-125418
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Informática
orbit prediction
error position estimation
debris
data accuracy
spellingShingle Ciencias Informáticas
Informática
orbit prediction
error position estimation
debris
data accuracy
Puente, Cristina
Sáenz Nuño, María
Villa Monte, Augusto
Olivas Varela, José Ángel
Satellite Orbit Prediction Using Big Data and Soft Computing Techniques to Avoid Space Collisions
topic_facet Ciencias Informáticas
Informática
orbit prediction
error position estimation
debris
data accuracy
description The number of satellites and debris in space is dangerously increasing through the years. For that reason, it is mandatory to design techniques to approach the position of a given object at a given time. In this paper, we present a system to do so based on a database of satellite positions according to their coordinates (x,y,z) for one month. We have paid special emphasis on the preliminary stage of data arrangement, since if we do not have consistent data, the results we will obtain will be useless, so the first stage of this work is a full study of the information gathered locating the missing gaps of data and covering them with a prediction. With that information, we are able to calculate an orbit error which will estimate the position of a satellite in time, even when the information is not accurate, by means of prediction of the satellite’s position. The comparison of two satellites over 26 days will serve to highlight the importance of the accuracy in the data, provoking in some cases an estimated error of 4% if the data are not well measured.
format Articulo
Articulo
author Puente, Cristina
Sáenz Nuño, María
Villa Monte, Augusto
Olivas Varela, José Ángel
author_facet Puente, Cristina
Sáenz Nuño, María
Villa Monte, Augusto
Olivas Varela, José Ángel
author_sort Puente, Cristina
title Satellite Orbit Prediction Using Big Data and Soft Computing Techniques to Avoid Space Collisions
title_short Satellite Orbit Prediction Using Big Data and Soft Computing Techniques to Avoid Space Collisions
title_full Satellite Orbit Prediction Using Big Data and Soft Computing Techniques to Avoid Space Collisions
title_fullStr Satellite Orbit Prediction Using Big Data and Soft Computing Techniques to Avoid Space Collisions
title_full_unstemmed Satellite Orbit Prediction Using Big Data and Soft Computing Techniques to Avoid Space Collisions
title_sort satellite orbit prediction using big data and soft computing techniques to avoid space collisions
publishDate 2021
url http://sedici.unlp.edu.ar/handle/10915/125418
https://www.mdpi.com/2227-7390/9/17/2040
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