Improved urban navigation with shadow matching and specular matching

Kirsten L. Strandjord, Penina Axelrad, Shan Mohiuddin

Peer Reviewed

Abstract:	As the dependence of Global Navigation Systems (GNSS) increases, so does a growing demand for GNSS accuracy in urban environments. This research aims to improve navigation in these environments by integrating non-line-of-sight signals, building models, and measured signal to noise ratios in ways not typically used in GNSS positioning. We propose a technique of combining elements of shadow matching, non-line-of-sight signal prediction through ray tracing, and collaborative navigation. A specularity metric is developed, which predicts the likelihood of building reflections resulting in non-line-of-sight signal reception, and is used in conjunction with shadow matching techniques to improve positioning. A framework for implementing these approaches is presented and demonstrated using improved positioning techniques built and tested using real-world data collected in urban surroundings.
Published in:	NAVIGATION, Journal of the Institute of Navigation, Volume 67, Number 3
Pages:	547 - 566
Cite this article:	Export Citation https://doi.org/10.1002/navi.378
Full Paper:	ION Members: Free Download Non-Members: Free Download Sign In