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Inverse modelling of GNSS multipath signals

Joakim Strandberg (Institutionen för rymd-, geo- och miljövetenskap, Onsala rymdobservatorium)
Gothenburg : Chalmers University of Technology, 2017.

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.

Nyckelord: sea ice, reflectometry, sea level, GNSS

Denna post skapades 2017-07-06. Senast ändrad 2017-07-07.
CPL Pubid: 250550


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Institutioner (Chalmers)

Institutionen för rymd-, geo- och miljövetenskap, Onsala rymdobservatorium


Multidisciplinär geovetenskap
Oceanografi, hydrologi, vattenresurser

Chalmers infrastruktur

Onsala rymdobservatorium

Relaterade publikationer

Inkluderade delarbeten:

Improving GNSS-R sea level determination through inverse modeling of SNR data

Inverse modelling of GNSS multipath for sea level measurements - initial results


Datum: 2017-09-07
Tid: 13:30
Lokal: EC-lecture hall, Hörsalsvägen 11, Chalmers
Opponent: Prof. Kristine Larson, University of Colorado, US