Published

2022-02-07

A Modelling Study by Factorial Design on GNSS Positioning

Estudio de modelado por diseño factorial en posicionamiento de Sistemas Globales de Navegación Satelital

DOI:

https://doi.org/10.15446/esrj.v25n4.95060

Keywords:

factorial design, regression analysis, GNSS error sources, CORS (en)
diseño factorial; análisis de regresión; fuentes de error GNSS; estaciones de referencia en funcionamiento continuo; Sistemas Globales de Navegación Satelital (es)

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Although researchers have widely studied the analysis and modelling of error sources on Global Navigation Satellite Systems positioning, some of these errors have not been eliminated significantly and only some of the Global Navigation Satellite System’s data are modelled. The present work was undertaken to determine the effect of different variables, namely: season, the number of visible satellites, and dilution of precision on the efficiency of horizontal and vertical CORS (Continuously Operating Reference Stations) positioning. For this aim, the CORS data was collected at 14 different test points during 600 epochs with 1-second intervals. Factorial designs supply an efficient solution to understand the impact of several factors on a response variable. A full factorial design with three factors at two levels was applied for these purposes. According to the results of the full factorial design, all factors significantly affected the response variable. Also, the interaction effects of factors were analysed on the CORS horizontal and vertical positioning. The regression equations were obtained for all situations.

A pesar de que los investigadores han analizado y modelado ampliamente  las fuentes de error de posicionamiento en los Sistemas Globales de Navegación Satelital (GNSS, Global Navigation Satellite System), algunos de estos errores no se han eliminado significativamente. Y solo parte de esta información de los Sistemas Satelitales de Navegación Global ha sido modelada. Este trabajo se realiza con el fin de determinar los efectos de diferentes variables: temporada, número de satélites visibles, e imprecisión en la eficiencia de posicionamiento horizontal y vertical CORS  (estaciones de referencia en funcionamiento continuo). La información CORS se recolectó en 14 escenarios de prueba durante 600 períodos y con intervalos de un segundo para este objetivo. Los diseños factoriales proveen una solución eficiente para entender el impacto de varios factores ante una respuesta variable. En este trabajo se aplicó un diseño factorial completo con tres factores en dos niveles. Los efectos principales y de interacción de factores se analizaron con el posicionamiento CORS horizontal y vertical. De acuerdo con los resultados del diseño factorial completo, mientras que los efectos principales y de interacción de factores afectaron significativamente el error de posicionamiento horizontal, algunos efectos principales y de interacción de factores no afectaron el posicionamiento vertical CORS. También las ecuaciones de regresión se obtuvieron para todas las situaciones con el fin de investigar los otros niveles de factores seleccionados en la respuesta de variables.

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APA

Ilci, V. and Sisman, Y. (2022). A Modelling Study by Factorial Design on GNSS Positioning. Earth Sciences Research Journal, 25(4), 391–396. https://doi.org/10.15446/esrj.v25n4.95060

ACM

[1]
Ilci, V. and Sisman, Y. 2022. A Modelling Study by Factorial Design on GNSS Positioning. Earth Sciences Research Journal. 25, 4 (Feb. 2022), 391–396. DOI:https://doi.org/10.15446/esrj.v25n4.95060.

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Ilci, V.; Sisman, Y. A Modelling Study by Factorial Design on GNSS Positioning. Earth sci. res. j. 2022, 25, 391-396.

ABNT

ILCI, V.; SISMAN, Y. A Modelling Study by Factorial Design on GNSS Positioning. Earth Sciences Research Journal, [S. l.], v. 25, n. 4, p. 391–396, 2022. DOI: 10.15446/esrj.v25n4.95060. Disponível em: https://revistas.unal.edu.co/index.php/esrj/article/view/95060. Acesso em: 20 oct. 2024.

Chicago

Ilci, Veli, and Yasemin Sisman. 2022. “A Modelling Study by Factorial Design on GNSS Positioning”. Earth Sciences Research Journal 25 (4):391-96. https://doi.org/10.15446/esrj.v25n4.95060.

Harvard

Ilci, V. and Sisman, Y. (2022) “A Modelling Study by Factorial Design on GNSS Positioning”, Earth Sciences Research Journal, 25(4), pp. 391–396. doi: 10.15446/esrj.v25n4.95060.

IEEE

[1]
V. Ilci and Y. Sisman, “A Modelling Study by Factorial Design on GNSS Positioning”, Earth sci. res. j., vol. 25, no. 4, pp. 391–396, Feb. 2022.

MLA

Ilci, V., and Y. Sisman. “A Modelling Study by Factorial Design on GNSS Positioning”. Earth Sciences Research Journal, vol. 25, no. 4, Feb. 2022, pp. 391-6, doi:10.15446/esrj.v25n4.95060.

Turabian

Ilci, Veli, and Yasemin Sisman. “A Modelling Study by Factorial Design on GNSS Positioning”. Earth Sciences Research Journal 25, no. 4 (February 7, 2022): 391–396. Accessed October 20, 2024. https://revistas.unal.edu.co/index.php/esrj/article/view/95060.

Vancouver

1.
Ilci V, Sisman Y. A Modelling Study by Factorial Design on GNSS Positioning. Earth sci. res. j. [Internet]. 2022 Feb. 7 [cited 2024 Oct. 20];25(4):391-6. Available from: https://revistas.unal.edu.co/index.php/esrj/article/view/95060

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