O método PPP de posicionamento GNSS: desempenho e perspectivas

Abstract

The advance of technologies since 1960 and the integration of positioning systems in the 2010s have increased interest in positioning terrestrial features with high accuracy. In this context, there are several methods of performing the processing of GNSS (Global Navigation Satellite System) data that make it possible to achieve levels of high precision and accuracy, one of which is the Precise Point Positioning (PPP) method. It is in this scenario that the objective of the work of comparatively analyzing the different online solutions and desktop system using the PPP method considering the variables occupancy time, different recording rates and multi-constellations, in order to verify the influence of these on the estimated results. Several processing campaigns were carried out using as reference the coordinates of the GOGY station belonging to RBMC (Brazilian Continuous Monitoring Network). The processing was carried out in each of the platforms using the proposed variables and their estimated results were compatible with the reference system and times of the GOGY station, in order to analyze the accuracy of the results consistently estimated. The online platforms used were: AUPOS, OPUS, CSRS - CANADA, IGN - PPP and IBGE - PPP and desktop: RTKLIB and WaSoft. The main results showed that the variables time of occupation, elevation mask and multi-constellations influenced the results. The recording rate was shown to have no influence on the accuracy of the results. Through the time of occupation, there was an improvement in the results after 90 minutes of observation. The use of lifting mask showed millimetric differences in the accuracy of the results. The use of constellation integration enhanced the accuracy of the results and proved to be promising by the amount of data coverage. The highlight of the online platforms were IBGE - PPP and CSRS-CANADA, presenting accuracy slower than 0.01 centimeters in a short time of observation. The highlight of desktop platforms was by RTKLIB, for its amount of optional possibilities and data handling.