Analysis of static and dynamic GNSS multipath in rural area

Abstract

Presently, the development of autonomous vehicles, particularly in construction, fo cuses extensively on excavators. This thesis examines the impact of multipath and environmental factors on GNSS signals when a single GNSS antenna is mounted on an excavator. Signal Strength Indicator(SSI) data for Galileo and GPS, along side GPS carrier phase residuals from the multi-GNSS PPP software GipsyX, were utilized to analyze the environment’s influence and the effects stemming from the excavator and its arm orientation. The experiment took place at a farm near the Onsala Space Observatory, involving the daily rotation of the excavator’s arm in different directions and simulated digging scenarios. Analysis of GPS SSI data from RINEX files and GPS post-fit residuals unveiled a systematic effect associated with the excavator’s arm orientation. The discernible impact on SSI suggests the potential for predicting the arm’s orientation even be fore data processing. Furthermore, employing residuals enables modeling of effects and errors linked to diverse arm orientations, promising enhanced data processing accuracy. Notably, superior performance was achieved using the L2L signal, demon strating higher correlations among residuals with matching arm orientations. Using the L2L signal also yielded improved repeatability in position estimations. The study suggests that concurrent consideration of RMSE values and correlation coef ficients of SSIs and residuals could effectively forecast the arm’s orientation. The measurements were done in a rather simple rural area with few objects, modelling the effects and errors linked to various arm orientations in this kind of area holds promise for enhancing position estimation, both in the same kind of area and as well in more complex areas like cities with numerous reflective objects causing multipath effects or signal blockage