Details
| Original language | English |
|---|---|
| Pages (from-to) | 2401-2420 |
| Number of pages | 20 |
| Journal | Advances in space research |
| Volume | 68 |
| Issue number | 6 |
| Early online date | 4 May 2021 |
| Publication status | Published - 15 Sept 2021 |
Abstract
In Global Navigation Satellite (GNSS)-based positioning, a user within a region covered by a network of reference stations can take advantage of the network-estimated parameters. The use of State Space Representation (SSR) parameters as GNSS-augmentation is valuable for Network-Real Time Kinematic (N-RTK) positioning and enables the ambiguity resolution for Precise Point Positioning (PPP) in the so-called PPP-RTK. SSR atmospheric corrections, i.e. tropospheric and ionospheric delays, are commonly estimated for the approximate user position by interpolation from values estimated for the reference stations. Widely used techniques are Inverse Distance Weighted, Ordinary Kriging and Weighted Least Squares (WLS). In this work, we analyze the interpolation quality of such techniques during severe weather events and Traveling Ionospheric Disturbances (TID). Furthermore, we propose modified WLS methods taking advantage of the physical atmospheric behavior during such events. Here, we exploit the use of Numerical Weather Models for tropospheric horizontal gradients information, and estimated TID parameters like wavelength and direction of propagation. Firstly, the interpolation is assessed using simulations considering artificial and real network geometries. Secondly, the proposed techniques are evaluated in post-processing using real SSR parameters generated by network computation of GNSS measurements. As examples, two severe weather events in North Europe in 2017, and one TID event over Japan in 2019 have been analyzed. The interpolation of SSR tropospheric and ionospheric parameters is evaluated. Considering the reference station positions as rover locations, the application of the modified WLS approach reduces the root mean square error in up to 80% of the cases during sharp weather fluctuations. Also, the average error can be decreased in 64% of the cases during the TID event investigated. Improvements up to factors larger than two are observed. Furthermore, specific cases are isolated showing particular tropospheric variations where significant errors (e.g. larger than 1 cm) can be reduced up to 20% of the total amount. Finally, tropospheric and ionospheric messages are proposed to transmit to the user the information needed to implement the suggested interpolation properly.
Keywords
- Atmospheric interpolation, GNSS, SSR-based positioning, TID, ZTD
ASJC Scopus subject areas
- Engineering(all)
- Aerospace Engineering
- Physics and Astronomy(all)
- Astronomy and Astrophysics
- Earth and Planetary Sciences(all)
- Geophysics
- Earth and Planetary Sciences(all)
- Atmospheric Science
- Earth and Planetary Sciences(all)
- Space and Planetary Science
- Earth and Planetary Sciences(all)
- General Earth and Planetary Sciences
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In: Advances in space research, Vol. 68, No. 6, 15.09.2021, p. 2401-2420.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Mitigation of severe weather events and TID impact on the interpolation of SSR atmospheric parameters
AU - Darugna, Francesco
AU - Bolmgren, Karl H.A.
AU - Schmitz, Martin
AU - Schön, Steffen
AU - Wübbena, Jannes B.
AU - Wübbena, Gerhard
AU - Bruno, Jon
AU - Mitchell, Cathryn N.
N1 - Funding Information: The investigations were funded in the framework of the research program Training REsearch and Applications Network to Support the Ultimate Real-Time High Accuracy EGNSS Solution (TREASURE) project. TREASURE has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 722023. CNM acknowledges support from grant NE/P006450/1. LGLN-SAPOS and GFZ are acknowledged for providing the RINEX data of the LGLN network and the tropospheric products from numerical weather models, respectively. Special thanks also to Lennard Huisman (Kadaster Netherlands) for providing the NETPOS network data. Furthermore, Mitsubishi Electronics is acknowledged for providing the RINEX data of the GEONET network stations covering the Okinawa islands. Funding Information: The investigations were funded in the framework of the research program Training REsearch and Applications Network to Support the Ultimate Real-Time High Accuracy EGNSS Solution (TREASURE) project. TREASURE has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sk?odowska-Curie grant agreement No 722023. CNM acknowledges support from grant NE/P006450/1. LGLN-SAPOS and GFZ are acknowledged for providing the RINEX data of the LGLN network and the tropospheric products from numerical weather models, respectively. Special thanks also to Lennard Huisman (Kadaster Netherlands) for providing the NETPOS network data. Furthermore, Mitsubishi Electronics is acknowledged for providing the RINEX data of the GEONET network stations covering the Okinawa islands.
PY - 2021/9/15
Y1 - 2021/9/15
N2 - In Global Navigation Satellite (GNSS)-based positioning, a user within a region covered by a network of reference stations can take advantage of the network-estimated parameters. The use of State Space Representation (SSR) parameters as GNSS-augmentation is valuable for Network-Real Time Kinematic (N-RTK) positioning and enables the ambiguity resolution for Precise Point Positioning (PPP) in the so-called PPP-RTK. SSR atmospheric corrections, i.e. tropospheric and ionospheric delays, are commonly estimated for the approximate user position by interpolation from values estimated for the reference stations. Widely used techniques are Inverse Distance Weighted, Ordinary Kriging and Weighted Least Squares (WLS). In this work, we analyze the interpolation quality of such techniques during severe weather events and Traveling Ionospheric Disturbances (TID). Furthermore, we propose modified WLS methods taking advantage of the physical atmospheric behavior during such events. Here, we exploit the use of Numerical Weather Models for tropospheric horizontal gradients information, and estimated TID parameters like wavelength and direction of propagation. Firstly, the interpolation is assessed using simulations considering artificial and real network geometries. Secondly, the proposed techniques are evaluated in post-processing using real SSR parameters generated by network computation of GNSS measurements. As examples, two severe weather events in North Europe in 2017, and one TID event over Japan in 2019 have been analyzed. The interpolation of SSR tropospheric and ionospheric parameters is evaluated. Considering the reference station positions as rover locations, the application of the modified WLS approach reduces the root mean square error in up to 80% of the cases during sharp weather fluctuations. Also, the average error can be decreased in 64% of the cases during the TID event investigated. Improvements up to factors larger than two are observed. Furthermore, specific cases are isolated showing particular tropospheric variations where significant errors (e.g. larger than 1 cm) can be reduced up to 20% of the total amount. Finally, tropospheric and ionospheric messages are proposed to transmit to the user the information needed to implement the suggested interpolation properly.
AB - In Global Navigation Satellite (GNSS)-based positioning, a user within a region covered by a network of reference stations can take advantage of the network-estimated parameters. The use of State Space Representation (SSR) parameters as GNSS-augmentation is valuable for Network-Real Time Kinematic (N-RTK) positioning and enables the ambiguity resolution for Precise Point Positioning (PPP) in the so-called PPP-RTK. SSR atmospheric corrections, i.e. tropospheric and ionospheric delays, are commonly estimated for the approximate user position by interpolation from values estimated for the reference stations. Widely used techniques are Inverse Distance Weighted, Ordinary Kriging and Weighted Least Squares (WLS). In this work, we analyze the interpolation quality of such techniques during severe weather events and Traveling Ionospheric Disturbances (TID). Furthermore, we propose modified WLS methods taking advantage of the physical atmospheric behavior during such events. Here, we exploit the use of Numerical Weather Models for tropospheric horizontal gradients information, and estimated TID parameters like wavelength and direction of propagation. Firstly, the interpolation is assessed using simulations considering artificial and real network geometries. Secondly, the proposed techniques are evaluated in post-processing using real SSR parameters generated by network computation of GNSS measurements. As examples, two severe weather events in North Europe in 2017, and one TID event over Japan in 2019 have been analyzed. The interpolation of SSR tropospheric and ionospheric parameters is evaluated. Considering the reference station positions as rover locations, the application of the modified WLS approach reduces the root mean square error in up to 80% of the cases during sharp weather fluctuations. Also, the average error can be decreased in 64% of the cases during the TID event investigated. Improvements up to factors larger than two are observed. Furthermore, specific cases are isolated showing particular tropospheric variations where significant errors (e.g. larger than 1 cm) can be reduced up to 20% of the total amount. Finally, tropospheric and ionospheric messages are proposed to transmit to the user the information needed to implement the suggested interpolation properly.
KW - Atmospheric interpolation
KW - GNSS
KW - SSR-based positioning
KW - TID
KW - ZTD
UR - http://www.scopus.com/inward/record.url?scp=85106354462&partnerID=8YFLogxK
U2 - 10.1016/j.asr.2021.04.038
DO - 10.1016/j.asr.2021.04.038
M3 - Article
AN - SCOPUS:85106354462
VL - 68
SP - 2401
EP - 2420
JO - Advances in space research
JF - Advances in space research
SN - 0273-1177
IS - 6
ER -