GNSS positioning with multipath simulation using 3D surface model in Urban Canyon

This paper proposes a novel global navigation satellite system (GNSS) positioning technique that can be used by vehicles or pedestrians in urban canyon environments. With the launch of new positioning satellites, the availability of the GNSS is anticipated to improve, although, owing to the serious impact of multipath signals on positioning accuracy within urban canyon environments, the increased availability of satellite positioning will not necessarily correspond to higher precision positioning. Here, we propose a technique based on multipath simulation using a 3D digital surface model (DSM) for obtaining GNSS positioning in urban canyons where there are large reflection and diffraction multipath errors. To calculate a user's position using multipath simulation, it is necessary to accurately predetermine their position, as the multipath effect is highly dependent on the surrounding obstructions. A particle filter, in which a number of hypotheses of user position are created, is used to solve this problem and allow multipath simulation to estimate the position. In the positioning process, a comparison is made between the signal-to-noise ratio (SNR) estimated by propagation loss within the 3D DSM and the observed SNR. For more correct hypotheses of a particle's position, these two values of the SNR will converge, as signal propagation will have been estimated more accurately, and such particles are given larger weights. Finally, an accurate user position can be estimated through a resampling process based on these particle weights. In order to confirm the effectiveness of this proposed technique, a static positioning test was performed in an urban canyon. The results of this assessment show that the proposed technique is effective and offers increased positioning accuracy in urban environments in which large reflection and diffraction multipath errors occur in GNSS signals.