Accuracy Enhancement of Consumer-Grade Global Positioning System (GPS) for Photogrammetric and City Mapping Determinations

Abstract

This paper address the fluctuation of a low-cost global GPS problem using an open platform of autonomous multi-rotors and particularly applying in location spotting from high accuracy UAV survey data. A city or urban planning requires a large scale of high precision survey data after data gathering using the photogrammetry method to regenerate the orthomosaic map. There was a problem when referring data from the map for access in real locations guided by a normal grade GPS receiver. The problem shows that the normal GPS cannot effectively work with high accuracy data. The aim of this study was to create a map location device using a normal GPS receiver for using high accuracy data from the industrial-grade UAV survey platform. We tested various GPS sensors applied with the Kalman filtering approach compared with the other source of field data then tuned the filter algorithm to improve the performance. The result shows that the Kalman filtering algorithm is presented significant reform to overcome the GPS data fluctuation problem and show a certain direction to perform the next step of a cost-effective map data pointer device.