Details
| Originalsprache | Englisch |
|---|---|
| Publikationsstatus | Veröffentlicht - 2021 |
| Veranstaltung | FIG e-Working Week 2021: Smart Surveyors for Land and Water Management - Challenges in a New Reality, Virtual, June 21–25 2021 - online, Niederlande Dauer: 20 Juni 2021 → 25 Juni 2021 https://fig.net/fig2021 |
Konferenz
| Konferenz | FIG e-Working Week 2021 |
|---|---|
| Kurztitel | FIG e-Working Week 2021 |
| Land/Gebiet | Niederlande |
| Zeitraum | 20 Juni 2021 → 25 Juni 2021 |
| Internetadresse |
Abstract
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
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2021. Beitrag in FIG e-Working Week 2021, Niederlande.
Publikation: Konferenzbeitrag › Paper › Forschung
}
TY - CONF
T1 - Improving Multi-GNSS Solutions with 3D Building Model and Tree Information
AU - Schaper, Anat
AU - Lin, Qianwen
AU - Janecki, Kim Sarah
AU - Mußgnug, Dennis
AU - Heiken, Max Leonard
AU - Chawda, Vimal
AU - Icking, Lucy Ling
AU - Kröger, Johannes
AU - Schön, Steffen
PY - 2021
Y1 - 2021
N2 - 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
AB - 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
KW - Multi-GNSS
KW - Urban Positioning
KW - 3DMA
KW - Tree Information
KW - Ray Tracing
KW - NLOS
KW - Weighting Model
KW - Signal Disturbance
M3 - Paper
T2 - FIG e-Working Week 2021
Y2 - 20 June 2021 through 25 June 2021
ER -