Abstract
goGPS is a free and open source satellite positioning software package aiming to provide a collaborative platform for research and teaching purposes. It was first published in 2009 and since then several related projects are on-going. Its objective is the investigation of strategies for enhancing the accuracy of low-cost single-frequency GPS receivers, mainly by relative positioning with respect to a base station and by a tailored extended Kalman filter working directly on code and phase observations. In this paper, the positioning algorithms implemented in goGPS are presented, emphasizing the modularity of the software design; two specific strategies to support the navigation with low-cost receivers are also proposed and discussed, namely an empirical observation weighting function calibrated on the receiver signal-to-noise ratio and the inclusion of height information from a digital terrain model as an additional observation in the Kalman filter. The former is crucial when working with high-sensitivity receivers, while the latter can significantly improve the positioning in the vertical direction. The overall goGPS positioning accuracy is assessed by comparison with a dual-frequency receiver and with the positioning computed by a standard low-cost receiver. The benefits of the calibrated weighting function and the digital terrain model are investigated by an experiment in a dense urban environment. It comes out that the use of goGPS and low-cost receivers leads to results comparable with those obtained by higher level receivers; goGPS has good performances also in a dense urban environment, where its additional features play an important role.
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