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 -