A Modelling Study by Factorial Design on GNSS Positioning


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İlçi V., ŞİŞMAN Y.

EARTH SCIENCES RESEARCH JOURNAL, vol.25, no.4, pp.391-396, 2021 (SCI-Expanded, Scopus) identifier identifier

  • Publication Type: Article / Article
  • Volume: 25 Issue: 4
  • Publication Date: 2021
  • Doi Number: 10.15446/esrj.v25n4.95060
  • Journal Name: EARTH SCIENCES RESEARCH JOURNAL
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Fuente Academica Plus, Geobase, Directory of Open Access Journals
  • Page Numbers: pp.391-396
  • Keywords: factorial design, regression analysis, GNSS error sources, CORS, GNSS, GEOMETRIC DILUTION, PRECISION GDOP, GPS, ACCURACY, NETWORK, PERFORMANCE, GLONASS
  • Open Archive Collection: AVESIS Open Access Collection
  • Ondokuz Mayıs University Affiliated: Yes

Abstract

Although researchers have widely studied the analysis and modeling of error sources on Global Navigation Satellite Systems positioning, some of these errors have not been eliminated significantly. Only some of the Global Navigation Satellite System's data are modeled. The present work was undertaken to determine the effect of different variables: season, the number of visible satellites, and dilution of precision on the efficiency of horizontal and vertical CORS (Continuously Operating Reference Stations) positioning. The CORS data was collected at 14 different test points during 600 epochs with 1-second intervals for this aim. 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. The main and the interaction effects of factors were analyzed on the CORS horizontal and vertical positioning. According to the full factorial design results, while all main and interaction effects of factors significantly affected the CORS horizontal positioning error, some elements did not affect the CORS vertical positioning error. Also, the regression equations were obtained for all situations to investigate the other level of selected factors in the response variables.