Snow Parameter Estimation with Multi-Frequency and Multi-Constellation
Global Navigation Satellite System Signals
Abstract
The Snow Water Equivalent (SWE) describes the amount of water stored in
snow. The SWE is a key parameter for various applications including
meteorological information systems, run-off predictions for hydro power
plants, and roof load monitoring. The SWE as well as the snow height and
liquid water content can be determined with Global Navigation Satellite
System (GNSS) signals. The set-up consists of two GNSS antennas where as
one antenna is placed on the ground below the snow and the second one is
placed on a pole above the snow, and serves as reference antenna. The
differential GNSS signals are affected by the relative position between
the antennas, the snow and the GNSS carrier phase ambiguities. The GNSS
signals are refracted at the air-snow interface, and attenuated and
delayed in the snow pack. The contribution of this talk is three-fold:
First, we have extended our snow parameter estimation [2,3] from a
single-frequency, dual constellation (GPS + Galileo) solution to a
multi-frequency, triple-constellation (GPS + Galileo + Beidou) solution
[1]. Secondly, we have used a Kalman filter to continuously estimate
the SWE and carrier phase ambiguities [1] instead of a least-squares
estimation. Third, the float ambiguity estimates are now fixed to
integer numbers with the Least-Squares Ambiguity Decorrelation
Adjustment (LAMBDA) method. The first results are very promising and
indicate that the measurement period for snow parameter estimation can
be reduced from several hours to less than 30 minutes. References:
[1] Julian Weiss: “Snow Parameter Estimation with Multi-Frequency
and Multi-Constellation GNSS”, Master thesis, Techn. Univ. Muenchen,
Germany, 2021. [2] Patrick Henkel, Franziska Koch, Florian Appel,
Heike Bach, Monika Prasch, Lino Schmid, Juerg Schweizer, and Wolfram
Mauser: “Snow Water Equivalent of Dry Snow Derived from GNSS Carrier
Phases“, in: IEEE Transactions on Geoscience and Remote Sensing, vol.
56, issue 6, pp. 3561 – 3572, Jun. 2018. [3] Franziska Koch,
Patrick Henkel, Florian Appel, Lino Schmid, Heike Bach, Markus Lamm,
Monika Prasch, Juerg Schweizer, and Wolfram Mauser: “Retrieval of snow
water equivalent, liquid water content, and snow height of dry and wet
snow by combining GPS signal attenuation and time delay“, in Water
Resources Research, vol. 55, issue 5, pp. 4465 – 4487, May 2019.