Processingof ground-basedGNSS Processingof ground-basedGNSS data toproducenear real-time(NRT) troposphericzenith data toproducenear real-time(NRT) troposphericzenith pathdelays(ZTD) pathdelays(ZTD) Jan Douša Jan Douša (jan.dousa (jan.dousa @pecny.cz @pecny.cz ) ) Geodetic Observatory Pecn Geodetic Observatory Pecn ý, ý, Research Institute of Geodesy, Topography and Cartography, Research Institute of Geodesy, Topography and Cartography, The The Czech Republic Czech Republic E-GVAP Workshop E-GVAP Workshop November 6, 2008 November 6, 2008
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Processing of groundbased GNSS Processing of groundbased GNSS
data to produce near realtime (NRT) tropospheric zenith data to produce near realtime (NRT) tropospheric zenith
GPS oscillator with fundamental GPS oscillator with fundamental frequency 10.23 MHz multiplied byfrequency 10.23 MHz multiplied by154x > 1575.42 MHz (L1)154x > 1575.42 MHz (L1)120x > 1227.60 MHz (L2)120x > 1227.60 MHz (L2)
code pseudorangecode pseudorangethe measure of the transit time from satellite to receiver using autocorrelation of received and replicated signal (the the measure of the transit time from satellite to receiver using autocorrelation of received and replicated signal (the time is coded in signal) time is coded in signal)
observablesobservables: : C1 = L1 C1 = L1 CC/A/A, , P1 = L1 P(Y) P1 = L1 P(Y), , P2P2 = L2 P(Y) and many others in future = L2 P(Y) and many others in future ≈≈ 1m absolute positioning for civil usage1m absolute positioning for civil usage
phase pseudorangephase pseudorangethe measure of the phase difference btw. received and replicated carrier frequencythe measure of the phase difference btw. received and replicated carrier frequency
observables: observables: L1, L2L1, L2 and others in future and others in futuresubcentimeterlevel relative positioningsubcentimeterlevel relative positioning
doppler datadoppler datathe measure of doppler shift due to a mutual motion of satellite and receiverthe measure of doppler shift due to a mutual motion of satellite and receiver
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Error sources for GNSSError sources for GNSS
SatellitesSatellites:: e ephphemeriemeriss, , clocks, differencial code biasesclocks, differencial code biases(AS(ASantispoofingantispoofing, , S/S/AAselective availabilityselective availability before 2000) before 2000)
ReceiversReceivers:: clocksclocks, , phase center offsets and variations, differencial code phase center offsets and variations, differencial code biasesbiases
EnvironmentEnvironment:: troposphere, ionosphere, multipath, Earth’s kinematicstroposphere, ionosphere, multipath, Earth’s kinematicsProcessingProcessing:: cycleslips in phases, model errors cycleslips in phases, model errors
→→ EliminationEliminationby observable differencesby observable differencesby introducing precise models and productsby introducing precise models and products
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Parameters in GNSS mathematical modelParameters in GNSS mathematical model
thus we have to handle somehow these parameters in GNSS processing:thus we have to handle somehow these parameters in GNSS processing:
• satellite and receiver positionsatellite and receiver position• satellite and receiver clock correctionssatellite and receiver clock corrections• Earth orientation parameters and geocenter coordinatesEarth orientation parameters and geocenter coordinates• satellite and receiver code differential biassatellite and receiver code differential bias• satellite and receiver phase center offsets and patternssatellite and receiver phase center offsets and patterns• troposphere effecttroposphere effect• ionosphere effectionosphere effect• ambiguitiesambiguities
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Observable differencesObservable differences
to eliminate some of the errors in mathematical GPSto eliminate some of the errors in mathematical GPS model model, we often create, we often create and use differences from the and use differences from the original observablesoriginal observables::
singledifferencesingledifference (SD) (SD) – – difference between two stationsdifference between two stations ( (baseline generationbaseline generation)), which, which eliminates the eliminates the satellite clock errors observed at both stationssatellite clock errors observed at both stations
doubledifferencedoubledifference (DD) (DD) – – difference between two SDs difference between two SDs ( (measurement to two satellites from the single measurement to two satellites from the single baselinebaseline)), which eliminates, which eliminates reciever clock errorsreciever clock errors
trippledifferencetrippledifference (TD) (TD) – diferen – diferences between two ces between two DD DD in different epochs, which is useful to detect in different epochs, which is useful to detect the phase skips (e.g. when signal from satellite was discontinued)the phase skips (e.g. when signal from satellite was discontinued)
the original observables we often call asthe original observables we often call as zerodifferencezerodifference (ZD) (ZD)
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GPSmeteorology conceptGPSmeteorology concept
GPS x NWP
we knowwe know precise receiver and orbit positions, precise receiver and orbit positions, we we eliminateeliminate i ionosonospherephere effect (receiver and satellite clock effect (receiver and satellite clock error), error), we introducewe introduce (PCVs, OCTIDE, ...) (PCVs, OCTIDE, ...)
we estimate: we estimate: zenith path tropospheric delay (receiver zenith path tropospheric delay (receiver and satellite clocks)and satellite clocks)
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GPS observation equationGPS observation equationBasic GPS carrier phase observable (scale to distance):Basic GPS carrier phase observable (scale to distance):
σσrecrecsat sat .. .. receiversatellite distance in vacuum receiversatellite distance in vacuum
((receiverreceiver and and satellite coordinates satellite coordinates))c c .. speed of light.. speed of lightδδsatsat, , δδrec rec .. .. satellite and receiver clocksatellite and receiver clock errors errors
λλ .. wavelength of the carrier phase.. wavelength of the carrier phasennrecrec
sat sat .. unknown initial phase .. unknown initial phase ambiguitiesambiguities
• user usually knows the models for the orbits, tides, etc.
Observations:Observations:
residualsresiduals
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Normal Equations (NEQsNormal Equations (NEQs))
normalnormal equationequation
parameter estimationparameter estimation
minimizing the residuals: minimizing the residuals: e‘ P e e‘ P e min. min.
parameters of interest (coordinates, parameters of interest (coordinates, troposphere, ...) troposphere, ...)
parameters to be eliminated (ambiguities)parameters to be eliminated (ambiguities)
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Sequential Adjustment: IdeaSequential Adjustment: Idea
often applied in two ways:often applied in two ways:
- time domain time domain
(sequential solutions)(sequential solutions)
- space domain space domain
(network clusters)(network clusters)
Processing of sequential Processing of sequential solutions :solutions :
identical identical with processing all with processing all observations in a common observations in a common adjustment, if there are no adjustment, if there are no correlationscorrelations of the original of the original observationsobservations
Adjustment of precise orbits & clocks Global network : ~20 IGS+German sites Input orbits: GFZ 3h Ultra-rapid (pred.)
CPU (Linux PC): ~6 to 8 minutes
Part 2 - PPP Analysis:
Estimation of trop. parameters Large set of parameters possible (high sampling rate, trop. gradients)
NEW: ‚slant delays‘ estimation CPU (Linux PC): <5 min for 220 sites
courtesy of Galina Dick (GFZ)courtesy of Galina Dick (GFZ)
GFZ EPOS SoftwareGFZ EPOS Software
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General network processing stepsGeneral network processing steps
• creating data batches (xhourly or sliding window)creating data batches (xhourly or sliding window)• data quality checkdata quality check• single point positioning for rough receisingle point positioning for rough receiverver clock synchroniz clock synchronizationation• network design by double differencing (clusters possible)network design by double differencing (clusters possible)• data screening for phase cycleslips, ambiguities set updata screening for phase cycleslips, ambiguities set up• iterative site & satelliteiterative site & satellite quality check and outliers rejectionquality check and outliers rejection• ionosphere product & ambiguity resolutionionosphere product & ambiguity resolution• reference frame realireference frame realizzation & coordinate estimationation & coordinate estimation• ZTD product generationZTD product generation
• preprocessingpreprocessing is based on twohours data batches is based on twohours data batches 1 hour redundancy with the previous run easier ambiguity resolution, 1 hour redundancy with the previous run easier ambiguity resolution, coordinates also for regularly ‘late’ RINEX ( > 30min ) coordinates also for regularly ‘late’ RINEX ( > 30min )
• normal equations (NEQ) normal equations (NEQ) – 1h for ZTD and 2h for coordinates– 1h for ZTD and 2h for coordinates• processingprocessing in clustersin clusters of the network of the network• coordinates coordinates are combined from last 28 days using 2hNEQs with ambiguity fixed, freeare combined from last 28 days using 2hNEQs with ambiguity fixed, free
network solution, IGS05 reference framenetwork solution, IGS05 reference frame• ZTD productZTD product based on last 12h stacking of 1hNEQs based on last 12h stacking of 1hNEQs• ionosphere product ionosphere product for ambiguity resolutionfor ambiguity resolution
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GOP processing schemeGOP processing scheme
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Ambiguity resolution in near realtimeAmbiguity resolution in near realtime• initial phase ambiguities represent a huge number ( > 90% !) of necessarilly estimated initial phase ambiguities represent a huge number ( > 90% !) of necessarilly estimated
parameters in mathematical GPS modelparameters in mathematical GPS model• in network solution, they can be resolved for integer numbers, which has strong impact in network solution, they can be resolved for integer numbers, which has strong impact
for the coordinate estimation in shorttime dataspan for the coordinate estimation in shorttime dataspan • ambituity resolution depends on timewindow and baseline lenghtambituity resolution depends on timewindow and baseline lenght• in GOP solution, for example, the ambiguities are resolved for in GOP solution, for example, the ambiguities are resolved for 70% in total70% in total within within
twohour data batch applying twostep approach (twohour data batch applying twostep approach (widelane ambiguitieswidelane ambiguities at at MelbourneWubbenna phase+code linear combination resolved in 8090% and MelbourneWubbenna phase+code linear combination resolved in 8090% and narrownarrowlane ambiguitieslane ambiguities at ionospherefree phase linear combination resolved with 70% at ionospherefree phase linear combination resolved with 70% success) success)
• resolved ambiguities are introduced ‘as known’ at least for the official coordinate resolved ambiguities are introduced ‘as known’ at least for the official coordinate estimation (estimation (North/East/UpNorth/East/Up coordinate repeatability improved from 10/10/25mm to coordinate repeatability improved from 10/10/25mm to 6/6/16mm6/6/16mm) )
• a positive bias of aprox. 1mm observed in ZTD solutions btw ambituity free and fix a positive bias of aprox. 1mm observed in ZTD solutions btw ambituity free and fix solution !solution !
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NRT coordinate solutionsNRT coordinate solutionsThe coordinates, which are ‘fixed’ or ‘tightly constrained’ in NRT ZTD solution should be as The coordinates, which are ‘fixed’ or ‘tightly constrained’ in NRT ZTD solution should be as
good as possible ( good as possible ( ≈≈ 3:1 for CRD:ZTD) 3:1 for CRD:ZTD)example: GOP solution for the coordinatesexample: GOP solution for the coordinates• the coordinates are based on ambiguity fixed solution using last 28 days of twohourly the coordinates are based on ambiguity fixed solution using last 28 days of twohourly
NEQs, the solution is updated every hour.NEQs, the solution is updated every hour.• the coordinates are expressed in local datum close to the last ITRF realization by IGS the coordinates are expressed in local datum close to the last ITRF realization by IGS
(currently IGS05) by applying the Helmert transformation (fidutial stations are (currently IGS05) by applying the Helmert transformation (fidutial stations are iteratively checked)iteratively checked)
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Troposphere model – Bernese GPS softwareTroposphere model – Bernese GPS software
Slant tropospheric path delays = wet + dry (hydrostatic) are mapped into zenith using a Slant tropospheric path delays = wet + dry (hydrostatic) are mapped into zenith using a mapping function (mf) mapping function (mf)
where ZHD can be well a priori estimated if atmospheric pressure and station heiht+latitude are where ZHD can be well a priori estimated if atmospheric pressure and station heiht+latitude are
known (e.g. Saastamoinen, 1972)known (e.g. Saastamoinen, 1972)
Because its variability, ZWD should be estimated for baselines > 20kmBecause its variability, ZWD should be estimated for baselines > 20km
Extended model could apply additionally the azimuthal dependency expressed as horizontal Extended model could apply additionally the azimuthal dependency expressed as horizontal
∂∂ mfmfWW//∂∂ z [ G z [ GNN cos(A) + Gcos(A) + GEE sin(A)] [A = azimuth]sin(A)] [A = azimuth]
Constant or Constant or piecewise linear functionpiecewise linear function is is applied for ZTDapplied for ZTD
Standard atmosphere (or insitu atm. pres. measurement) for a priori ZHDStandard atmosphere (or insitu atm. pres. measurement) for a priori ZHD
Dry and wet ‘Niell’ mf (‘Global’ or ‘Vienna’ mf in future) Dry and wet ‘Niell’ mf (‘Global’ or ‘Vienna’ mf in future)
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Troposphere model – impact study exampleTroposphere model – impact study exampleSome impacts in past using older models:Some impacts in past using older models: 2.2. no a priori model (zero value) and dry Niell mapping function used for the total zenith delay estimated (used no a priori model (zero value) and dry Niell mapping function used for the total zenith delay estimated (used
until May 2005).until May 2005).3.3. a priori ZHD based on standard atmosphere and wetNiell mapping function estimating ZTD (hopefully a priori ZHD based on standard atmosphere and wetNiell mapping function estimating ZTD (hopefully
most of the ZWD).most of the ZWD).→ bias variablebias variable in time and space in time and space
Another sitedependentAnother sitedependentbias was introduced bias was introduced in 2006 due to changingin 2006 due to changingrelative relative →→ absolute absolutePhase Center VariationsPhase Center Variationsand Offsets model usedand Offsets model used(upto 5mm)(upto 5mm)
• ZTDs for every hour (HH:00 + HH:59)ZTDs for every hour (HH:00 + HH:59)• a linear trend is considered between the valuesa linear trend is considered between the values• coordinates are heavily constrained to our estimated values realizing the IGb00 coordinates are heavily constrained to our estimated values realizing the IGb00
reference frame and written to the COST 716 format.reference frame and written to the COST 716 format.• ZTD product filtering:ZTD product filtering:
– Sites with less than 4 hours of data in ZTD solution are excluded from the productSites with less than 4 hours of data in ZTD solution are excluded from the product– Sites with less than 2 days of data in coordinate solution are excluded. Sites with less than 2 days of data in coordinate solution are excluded.
• ambiguityfree (AF) and ambiguityfixed (AX) ZTD solutions are provided ambiguityfree (AF) and ambiguityfixed (AX) ZTD solutions are provided (officially AF), both using the same a priori coordinates values (ambiguityfixed).(officially AF), both using the same a priori coordinates values (ambiguityfixed).
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Requirements:Requirements:hourly GNSS data (IGS, EPN, national,...)
correlation with respect to previous estimates (physical, via processing, possible constraints – depends on timeresolution)
Other important models:Other important models:ocean and Earth tides (station coordinate, geocentr, satellite orbits)
receiver and satellite phase center offsets and variations
troposphere mapping function
2nd, 3rd order ionosphere
many others especially
in precise orbit determination
NNear realtime ear realtime aspects of aspects of ZTDZTD estimation estimation
last hour
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GNSS hourly data availabilityGNSS hourly data availability
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predominantly IGS ultrarapid orbits usedpredominantly IGS ultrarapid orbits used
Requirements on predicted orbits for ZTDRequirements on predicted orbits for ZTD
errors in ZTD
2001
2008
Synthetic error in orbit positionSynthetic error in orbit position 1m in alongtrack 1m in crosstrack 1m in radial (mostly eliminated in DD)
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ZTD results PPP vs NetworkZTD results PPP vs Network
ZIMM and GOPE – one of the 12 ‘supersites’ZIMM and GOPE – one of the 12 ‘supersites’
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Some ZTD/PWV comparison at GOPSome ZTD/PWV comparison at GOP20012003 comparison20012003 comparisonNRT x postprocessingNRT x postprocessing
StdDev : StdDev : 47mm 47mm
BBiasias : : 13mm13mm
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weeklyweekly Sdev and Bias Sdev and Bias GPS ZTD from GOP near realtime GPS ZTD from GOP near realtime NWM Hirlam from DMI NWM Hirlam from DMI