Eventos Anais de eventos
DINAME 2023
XIX International Symposium on Dynamic Problems of Mechanics
Comparative analysis between tropospheric models for GNSS positioning in Brazilian territory
Submission Author:
Ludmila Aparecida de Oliveira , MG
Co-Authors:
Ludmila Aparecida de Oliveira, Izadora Ramos, FELIPE OLIVEIRA E SILVA, Danilo Alves de Lima
Presenter: FELIPE OLIVEIRA E SILVA
doi://10.26678/ABCM.DINAME2023.DIN2023-0132
Abstract
Global Navigation Satellite Systems (GNSS) can be applied in several areas, such as precision agriculture, vehicular navigation, intelligent/autonomous systems and air traffic control. Despite being robust, there are many sources of error that corrupt the GNSS signals used for positioning. Evaluating, controlling and mainly eliminating such sources of errors become crucial activities for these systems to reach the level of precision required in the aforementioned applications. Among the most relevant sources of error corrupting GNSS signals, there is the delay imposed on its observables when the signal propagates through the tropospheric layer of the Earth. For real-time positioning applications, the approach traditionally used to mitigate such delays is the use of empirical models based on measurements and/or estimates of atmospheric parameters. Although several models have been proposed over the years, there are few works that present a comparative study of their performance, especially in the national territory. Therefore, this work presents as a contribution, a comparative analysis, in Brazilian territory, between eight models that aim to mitigate the propagation errors of GNSS signals through the troposphere. In order to verify the effectiveness of each of these models and to determine which one presents the best performance, experimental results are presented based on GNSS data collected from reference stations belonging to the Brazilian Network for Continuous Monitoring (RBMC) of GNSS signals, which are evaluated for the Root Mean Square Errors (RMSE) of individual, horizontal and total positions. Among the models analyzed, one verifies that the one proposed by the University of Brunswick 3 (UNB3) is the one with the best performance.
Keywords
GNSS, tropospheric models, RMSE, UNB3
