Application the SBAS/EGNOS Corrections in UAV Positioning

The paper presents a new concept of determining the resultant position of a UAV (Unmanned Aerial Vehicle) based on individual SBAS (Satellite-Based Augmentation System) determinations from all available EGNOS (European Geostationary Navigation Overlay Service) satellites for the SPP (Single Point Positioning) code method. To achieve this, the authors propose a weighted mean model to integrate EGNOS data. The weighted model was based on the inverse of the square of the mean position error along the component axes of the BLh ellipsoidal frame. The calculations included navigation data from the EGNOS S123, S126, S136 satellites. In turn, the resultant UAV position model was determined using the Scilab v.6.0.0 software. Based on the proposed computational strategy, the mean values of the UAV BLh coordinates' standard deviation were better than 0.2 m (e.g., 0.0000018 degrees = 0.01 '' in angular measurement). Additionally, the numerical solution used made it possible to increase the UAV's position accuracy by about 29% for Latitude, 46% for Longitude and 72% for ellipsoidal height compared to the standard SPP positioning in the GPS receiver. It is also worth noting that the standard deviation of the UAV position calculated from the weighted mean model improved by about 21 divided by 50% compared to the arithmetic mean model's solution. It can be concluded that the proposed research method allows for a significant improvement in the accuracy of UAV positioning with the use of EGNOS augmentation systems.

Automated summary

This study introduces a new method to improve UAV positioning accuracy by integrating EGNOS data. The results show that using the weighted mean model significantly improves UAV positioning accuracy compared to the standard SPP positioning method, with an increase of 29% in Latitude, 46% in Longitude, and 72% in ellipsoidal height.