Research Online: Urban positioning accuracy enhancement using 3D buildings model

Research Online: Urban positioning accuracy enhancement using 3D buildings model

Above: The constructed 3D model for 26 buildings; below: illustration of the direction of recording of surfaces. Click to enlarge.

By Nesreen I. Ziedan, Zagazig University, Egypt / Presented at ION GNSS+ 2017, September 2017

Multipath is a major source of positioning accuracy degradation in urban areas. Advances in 3D mapping and the availability of 3D city models have encouraged a set of new techniques for multipath mitigation.

This paper presents three algorithms to enhance the accuracy of urban positioning using all the available line-of-sight, multipath and non-line-of-sight signals:

■ An accelerated ray tracing technique that first eliminates the 3D surfaces that are invisible with respect to a position, and then analyzes the visible surfaces to predict the existence and path lengths of reflected signals. The ray tracing algorithm is applied on the possible range of positions.

■ A Markov Chain Monte Carlo-based algorithm that applies both the Gibbs sampler and the Metropolis-Hastings technique to analyze the received correlated signals to estimate the delays of reflected signals for all the received signals.

■ A Van Rossum-based technique that measures the discrepancy between the estimated delays and the predicted ones at a range of possible positions, where the position that generates the minimum discrepancy is taken as the estimated position. Test results indicate the ability of the algorithms to successfully utilize reflected signals to enhance urban positioning accuracy.


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