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Enhancing Least Squares GNSS Positioning with 3D Mapping without Accurate Prior Knowledge

Adjrad, M; Groves, PD; (2017) Enhancing Least Squares GNSS Positioning with 3D Mapping without Accurate Prior Knowledge. Navigation, Journal of the Institute of Navigation , 64 (1) pp. 75-91. 10.1002/navi.178. Green open access

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Abstract

GNSS positioning performance in dense urban areas is severely degraded due to the obstruction and reflection of the signals by the surrounding buildings. A basic GNSS position solution can exhibit errors of tens of meters, sometimes more. Here, 3D mapping is used to aid conventional ranging-based GNSS positioning. Terrain height-aiding contributes an additional virtual ranging measurement to the position solution. In addition, 3D city models predict Non-Line-Of-Sight (NLOS) reception over a large search area. The resulting NLOS probabilities aid a consistency checking algorithm that selects and weights the signal used for the final position solution. Iteration then refines the position solution. Practical test results demonstrate improvement in the horizontal and vertical accuracy of conventional ranging-based GNSS positioning in urban areas by a factor of 2.5 and 5, respectively. Using the new technique, the Root Mean Square (RMS) position error in dense urban areas was found to be 20.8 m horizontally and 12.2 m vertically.

Type: Article
Title: Enhancing Least Squares GNSS Positioning with 3D Mapping without Accurate Prior Knowledge
Open access status: An open access version is available from UCL Discovery
DOI: 10.1002/navi.178
Publisher version: http://doi.org/10.1002/navi.178
Language: English
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng
URI: https://discovery.ucl.ac.uk/id/eprint/1557339
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