Inverse modelling of GNSS multipath signals

Measuring the world around us is necessary to observe and understand the changes that occur in our environment. A widely distributed network of measurement stations can help us to understand ongoing and predict future climate change. GNSS reflectometry has the capacity of providing data from all ove...

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Main Author: Strandberg, Joakim
Language:unknown
Published: 2017
Subjects:
Online Access:https://research.chalmers.se/en/publication/250550
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spelling ftchalmersuniv:oai:research.chalmers.se:250550 2023-05-15T18:17:46+02:00 Inverse modelling of GNSS multipath signals Strandberg, Joakim 2017 text https://research.chalmers.se/en/publication/250550 unknown https://research.chalmers.se/en/publication/250550 Remote Sensing Oceanography Hydrology Water Resources Signal Processing Geosciences Multidisciplinary GNSS reflectometry sea ice sea level 2017 ftchalmersuniv 2022-12-11T07:01:42Z Measuring the world around us is necessary to observe and understand the changes that occur in our environment. A widely distributed network of measurement stations can help us to understand ongoing and predict future climate change. GNSS reflectometry has the capacity of providing data from all over the world, as there are already many GNSS stations established and operated for navigational and meteorological purposes. This thesis presents a new way of retrieving environmental data from GNSS signal-to-noise ratio measurements which has the capability to provide new types of measurements. The method is based on inverse modelling of the signal-to-noise ratio in order to retrieve physical parameters of reflecting surfaces around GNSS installations. It is successfully demonstrated that the method improves the precision of the GNSS reflectometry derived sea surface height measurements significantly. By using the signal-to-noise ratio pattern, it is also — for the first time — demonstrated that it is possible to use GNSS reflectometry to detect coastal sea ice. Other/Unknown Material Sea ice Chalmers University of Technology: Chalmers research
institution Open Polar
collection Chalmers University of Technology: Chalmers research
op_collection_id ftchalmersuniv
language unknown
topic Remote Sensing
Oceanography
Hydrology
Water Resources
Signal Processing
Geosciences
Multidisciplinary
GNSS
reflectometry
sea ice
sea level
spellingShingle Remote Sensing
Oceanography
Hydrology
Water Resources
Signal Processing
Geosciences
Multidisciplinary
GNSS
reflectometry
sea ice
sea level
Strandberg, Joakim
Inverse modelling of GNSS multipath signals
topic_facet Remote Sensing
Oceanography
Hydrology
Water Resources
Signal Processing
Geosciences
Multidisciplinary
GNSS
reflectometry
sea ice
sea level
description Measuring the world around us is necessary to observe and understand the changes that occur in our environment. A widely distributed network of measurement stations can help us to understand ongoing and predict future climate change. GNSS reflectometry has the capacity of providing data from all over the world, as there are already many GNSS stations established and operated for navigational and meteorological purposes. This thesis presents a new way of retrieving environmental data from GNSS signal-to-noise ratio measurements which has the capability to provide new types of measurements. The method is based on inverse modelling of the signal-to-noise ratio in order to retrieve physical parameters of reflecting surfaces around GNSS installations. It is successfully demonstrated that the method improves the precision of the GNSS reflectometry derived sea surface height measurements significantly. By using the signal-to-noise ratio pattern, it is also — for the first time — demonstrated that it is possible to use GNSS reflectometry to detect coastal sea ice.
author Strandberg, Joakim
author_facet Strandberg, Joakim
author_sort Strandberg, Joakim
title Inverse modelling of GNSS multipath signals
title_short Inverse modelling of GNSS multipath signals
title_full Inverse modelling of GNSS multipath signals
title_fullStr Inverse modelling of GNSS multipath signals
title_full_unstemmed Inverse modelling of GNSS multipath signals
title_sort inverse modelling of gnss multipath signals
publishDate 2017
url https://research.chalmers.se/en/publication/250550
genre Sea ice
genre_facet Sea ice
op_relation https://research.chalmers.se/en/publication/250550
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