Issue |
J. Space Weather Space Clim.
Volume 7, 2017
Space weather effects on GNSS and their mitigation
|
|
---|---|---|
Article Number | A26 | |
Number of page(s) | 14 | |
DOI | https://doi.org/10.1051/swsc/2017020 | |
Published online | 24 October 2017 |
Research Article
Multi-frequency GNSS robust carrier tracking for ionospheric scintillation mitigation
1
Centre Tecnològic de Telecomunicacions de Catalunya (CTTC/CERCA),
Barcelona, Spain
2
Department of Electrical and Computer Eng., Northeastern University,
Boston,
MA
02115, USA
3
European Space Agency (ESA),
Noordwijk,
The Netherlands
* Corresponding author: jvila@cttc.cat
Received:
11
May
2017
Accepted:
14
August
2017
Ionospheric scintillation is the physical phenomena affecting radio waves propagating from the space through the ionosphere to earth. The signal distortion induced by scintillation can pose a major threat to some GNSS application. Scintillation is one of the more challenging propagation scenarios, particularly affecting high-precision GNSS receivers which require high quality carrier phase measurements; and safety critical applications which have strict accuracy, availability and integrity requirements. Under ionospheric scintillation conditions, GNSS signals are affected by fast amplitude and phase variations, which can compromise the receiver synchronization. To take into account the underlying correlation among different frequency bands, we propose a new multivariate autoregressive model (MAR) for the multi-frequency ionospheric scintillation process. Multi-frequency GNSS observations and the scintillation MAR are modeled in state-space, allowing independent tracking of both line-of-sight phase variations and complex gain scintillation components. The resulting joint synchronization and scintillation mitigation problem is solved using a robust nonlinear Kalman filter, validated using real multi-frequency scintillation data with encouraging results.
Key words: GNSS / ionospheric scintillation / multivariate AR modeling / robust tracking / carrier phase synchronization / adaptive nonlinear Kalman filter
© J. Vilà-Valls et al., Published by EDP Sciences 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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