Abstract

The objective of this paper is to enhance the accuracy of urban positioning using all the available LOS, multipath, and NLOS signals. Three algorithms are presented to achieve this objective. The first algorithm is 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. The second algorithm is a Markov Chain Monte Carlo (MCMC) 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. The third algorithm is 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. Experimental tests are conducted at two different areas, with different characteristics. The first area is located at the campus of Zagazig University, Egypt, and the second area is located at the campus of Wuhan University, China. The results indicate the ability of the algorithms to successfully utilize reflected signals to enhance urban positioning accuracy.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.