Improving Multi-GNSS Solutions with 3D Building Model and Tree Information

authored by: Anat Schaper, Qianwen Lin, Kim Sarah Janecki, Dennis Mußgnug, Max Leonard Heiken, Vimal Chawda, Lucy Ling Icking, Johannes Kröger, Steffen Schön
Abstract: Positioning using multiple Global Navigation Satellite Systems (GNSS) offers a significant advantage, especially in dense urban areas. In particular in these areas, the combination of individual GNSS significantly increases the number of visible satellites and thus the GNSS availability for positioning.
However, signal interruptions, disturbances, and multipath effects due to buildings and trees still have an influence on positioning. To characterise this influence, we use a ray tracing algorithm to classify the observations into Line-of-Sight and Non-Line-of-Sight signals. For this purpose, a 3D building model of the city of Hanover and Open-Street-Map tree coordinates, the latter being supplemented by own measurements, are used.
In this paper, we focus on a multi-GNSS single point positioning algorithm that incorporates the environmental information. We perform adapted weighting models and compare the performance of these weightings with already established weighting schemes (considering satellite elevation, signal strength or unity weighting). In this way, we verify the effectiveness of these extended models. We show that incorporating environmental factors in the weighting models gives an improvement of up to 60% in terms of the 95% quantile of the 3D deviations to the ground truth. In fact, comparable accuracies to carrier-to-noise density dependent weighting can be achieved. Improving
Organisation(s): Institute of Geodesy
Type: Paper
Publication date: 2021
Publication status: Published
: Details in the research portal "Research@Leibniz University"

BibTeX

@conference{af83f6a2754c4400bed38b6886f16626,
title = "Improving Multi-GNSS Solutions with 3D Building Model and Tree Information",
abstract = "Positioning using multiple Global Navigation Satellite Systems (GNSS) offers a significant advantage, especially in dense urban areas. In particular in these areas, the combination of individual GNSS significantly increases the number of visible satellites and thus the GNSS availability for positioning.However, signal interruptions, disturbances, and multipath effects due to buildings and trees still have an influence on positioning. To characterise this influence, we use a ray tracing algorithm to classify the observations into Line-of-Sight and Non-Line-of-Sight signals. For this purpose, a 3D building model of the city of Hanover and Open-Street-Map tree coordinates, the latter being supplemented by own measurements, are used.In this paper, we focus on a multi-GNSS single point positioning algorithm that incorporates the environmental information. We perform adapted weighting models and compare the performance of these weightings with already established weighting schemes (considering satellite elevation, signal strength or unity weighting). In this way, we verify the effectiveness of these extended models. We show that incorporating environmental factors in the weighting models gives an improvement of up to 60% in terms of the 95% quantile of the 3D deviations to the ground truth. In fact, comparable accuracies to carrier-to-noise density dependent weighting can be achieved. Improving",
keywords = "Multi-GNSS, Urban Positioning, 3DMA, Tree Information, Ray Tracing, NLOS, Weighting Model, Signal Disturbance",
author = "Anat Schaper and Qianwen Lin and Janecki, {Kim Sarah} and Dennis Mu{\ss}gnug and Heiken, {Max Leonard} and Vimal Chawda and Icking, {Lucy Ling} and Johannes Kr{\"o}ger and Steffen Sch{\"o}n",
year = "2021",
language = "English",
note = "FIG e-Working Week 2021 : Smart Surveyors for Land and Water Management - Challenges in a New Reality, Virtual, June 21–25 2021, FIG e-Working Week 2021 ; Conference date: 20-06-2021 Through 25-06-2021",
url = "https://fig.net/fig2021",
}