Global Navigation Satellite System data processing at near real time Martin Imrišek Slovak University of Technology in Bratislava Department of Theoretical Geodesy & Slovak Hydrometeorological Institute martin.imrisek@stuba.sk September 19, 2017 Martin Imrišek (SUT & SHMI) GNSS data processing September 19, 2017 1 / 20
Introduction Martin Imrišek (SUT & SHMI) GNSS data processing September 19, 2017 2 / 20
Data processing GNSS data processing may be divided from latency point of view on: Final processing, Near real time processing, Real time processing. GNSS data processing may be divided also from processing strategy point of view on: Precise network positioning, Precise point positioning. Martin Imrišek (SUT & SHMI) GNSS data processing September 19, 2017 3 / 20
Routine processing GPS and GLONASS, network processing at near real time, MAX OBS baseline strategy, 32 min latency, 59 stations are being processed every hour, 40 stations are from Euref network, 6 stations are from IGS network, 13 stations are from Austrian, Czech, Hungarian and Slovak national networks of permanent GNSS stations. http://space.vm.stuba.sk/pwvgraph/ Martin Imrišek (SUT & SHMI) GNSS data processing September 19, 2017 4 / 20
Routine processing 52.5 N PTBB 50.0 N 47.5 N WROC CLIB POUS CRAK BISK KATO GOPE CPAR KRA1 SULP CFRMZYWI KUZA LIE1 USDL WTZRVACO TUBO SKSL SKSK SKLMGANP SKTN KAME KOLS TELG SKSE BBYS KOSE PEMB UZHL LINZ MOP2 BASV VELS SKNR RISO TUWISUT1 DOPL HUVO SPRN PENC BAIA BUTE GRAZ 45.0 N ZOUF GSR1 PADO VEN1 PORE CAKO POZE OROS DEVA BUCU 42.5 N 10.0 E 12.5 E 15.0 E 17.5 E 20.0 E 22.5 E 25.0 E 27.5 E 30.0 E Martin Imrišek (SUT & SHMI) GNSS data processing September 19, 2017 5 / 20
Result comparison IGS stations Final Precise point positioning Bucuresti, Romania BUCU Gánovce, Slovakia GANP Graz, Austria GRAZ Uzhgorod, Ukraine UZHL Wettzell, Germany WTZR Zimmerwald, Switzerland ZIMM Differences are shifted about 2150 mm. Martin Imrišek (SUT & SHMI) GNSS data processing September 19, 2017 6 / 20
Result comparison Martin Imrišek (SUT & SHMI) GNSS data processing September 19, 2017 7 / 20
Result comparison Martin Imrišek (SUT & SHMI) GNSS data processing September 19, 2017 8 / 20
Result comparison Martin Imrišek (SUT & SHMI) GNSS data processing September 19, 2017 9 / 20
Result comparison Martin Imrišek (SUT & SHMI) GNSS data processing September 19, 2017 10 / 20
Result comparison Table: Statistic of differences BUCU GANP GRAZ Correlation +0.988 +0.988 +0.989 Minimum [mm] -38.0-33.8-30.1 Maximum [mm] 18.6 18.5 23.1 Average [mm] -2.13-1.29-1.26 Standard deviation [mm] 6.08 6.22 6.25 UZHL WTZR ZIMM Correlation +0.990 +0.989 +0.985 Minimum [mm] -18.7-25.0-23.0 Maximum [mm] 19.7 16.6 22.5 Average [mm] -0.36-0.59 0.14 Standard deviation [mm] 5.82 5.92 5.78 Martin Imrišek (SUT & SHMI) GNSS data processing September 19, 2017 11 / 20
ZTD data assimilation AROME Hungarian domain, grid point resolution 2.5 km and 60 pressure levels, GPS data assimilation is respecting ASSIMILATION OF GPS MOISTURE INFORMATION Mohamed Zied SASSI, 32 white listed stations (more incoming), static bias correction, only one GNSS data assimilation cycle at 12UTC 18th August 2017 was performed, NOGNSS and +GNSS 36 hours forecast. Martin Imrišek (SUT & SHMI) GNSS data processing September 19, 2017 12 / 20
ZTD data assimilation technical check Figure: Differences in specific humidity at 50th pressure level between guess and analysis at 12UTC 18th August 2017. Martin Imrišek (SUT & SHMI) GNSS data processing September 19, 2017 13 / 20
ZTD data assimilation technical check Figure: Differences in relative humidity between guess and analysis at SKLM and GANP permanent stations at 12UTC 18th August 2017. Martin Imrišek (SUT & SHMI) GNSS data processing September 19, 2017 14 / 20
ZTD data assimilation technical check Figure: Differences in temperature between guess and analysis at SKLM and GANP permanent stations at 12UTC 18th August 2017. Martin Imrišek (SUT & SHMI) GNSS data processing September 19, 2017 15 / 20
ZTD data assimilation technical check Figure: Differences in specific humidity between guess and analysis at SKLM and GANP permanent stations at 12UTC 18th August 2017. Martin Imrišek (SUT & SHMI) GNSS data processing September 19, 2017 16 / 20
ZTD data assimilation technical check Figure: 24h accumulated rainfall from 00UTC 19th August 2017. NOGNSS (top left), +GNSS (top right), differences (bottom left) and INCA (bottom right). Martin Imrišek (SUT & SHMI) GNSS data processing September 19, 2017 17 / 20
Conclusions Local GNSS processing designed for SHMI purposes, obtained ZTD are comparable with IGS final PPP product, first 3DVAR data assimilation studies on SHMI, result is not convincing from one assimilation cycle. Future perspectives : multiple cycle data assimilation case study, add more data types to assimilation. Big Thanks to Alena Trojáková and Máté Mile for support. I would be grateful for any feedback or advice. Martin Imrišek (SUT & SHMI) GNSS data processing September 19, 2017 18 / 20
Thank you for your attention. Martin Imrišek (SUT & SHMI) GNSS data processing September 19, 2017 19 / 20
New generation of permanent GNSS stations Martin Imrišek (SUT & SHMI) GNSS data processing September 19, 2017 20 / 20