Correcting GNSS multipath errors using a 3D surface model and particle filter

In this study, we propose a novel global navigation satellite system (GNSS) positioning technique that can be used in urban canyon environments where GNSS positioning is almost useless. Multipath signals, which are reflected or diffracted by objects such as buildings, are recognized as the most important causes of major positioning errors in urban environments. This problem has been investigated for many years. Various practical and popular signal correlator techniques can also help to mitigate multipath errors. However, if an antenna cannot receive a direct signal (line of sight signal), these techniques do not produce satisfactory results because they assume that the antenna mainly receives direct and multipath signals. Thus, we propose a novel GNSS positioning technique that can be used in multipath environments, which is based on a multipath error simulation using a 3D surface model of a building. To calculate a user's position based on multipath simulation, it is necessary to predetermine their position accurately because the multipath effect is highly dependent on the surrounding obstructions. Thus, a particle filter, which hypothesizes a number of user positions, is used to solve this problem, thereby allowing the multipath simulation to estimate the position. The proposed technique attempts to estimate a user's position by comparing the distance between the particle position and the point positioning solution using pseudoranges to correct the multipath error, which is estimated from the multipath simulation. The multipath error in the observed pseudorange depends on a signal correlator design, which is implemented using GNSS receivers. The consumer's GNSS receivers cannot be used to estimate multipath errors because the correlator is a black box. Therefore, we use a GNSS software receiver to implement the proposed techniques. A positioning test was performed in a real-world urban canyon environment, which confirmed the effectiveness of the proposed technique. The proposed technique is effective and it provides increased positioning accuracy in urban canyon environments that suffer from large reflection and diffraction multipath errors in GNSS signals.