Modeling

  • Modeling of tides, subdaily Earth rotation, and nutation are conforming with IERS Conventions 2010
  • Interpolation of ocean tidal loading to 342 constituents (HARDISP) according to IERS2010 conventions
  • S1/S2 atmosphere pressure loading tidal corrections
  • Center of mass corrections for ocean and atmospheric tidal loading
  • Use of various gravity fields easily implementable
  • DE405 ephemeris series for planets as well as the gravitational effect of ocean and solid Earth tides in the orbit integrator (ORBGEN)
  • Piece-wise linear troposphere parameter representation, with possibility to enforce continuous parameterization at session boundaries
  • A priori model for hydrostatic component of troposphere (mapped with dry-GMF or VMF1 mapping function)
  • Horizontal troposphere gradient parameters
  • Introduction of (globally) estimated troposphere delays on normal equation level
  • Ionosphere corrections from global or regional ionosphere maps
  • Higher order ionosphere corrections (2nd and 3rd order and ray bending) including scaling factors


Processing


The following list of processing features and characteristics can only be a selection on the very top level. It is related to the usual processing steps and some selected product aspects:


RINEX
  • Support RINEX 2.x and 3.x
  • Verification of the station name with respect to the filename
  • Extended checks of the RINEX headers with respect to an internal equipment database (the so-called "Station Information" file) for the receiver/antenna+radome type and number as well as the antenna height
  • Check the availability of antenna+radome phase center corrections
  • Automated exclusion of stations with equipment changes, or presenting a reduced data tracking, or with indicated data problems ("Problems" reported in a "Station Information" file) when importing the data.
Preprocessing
  • Detection and handling of inconsistencies between code and phase data regarding the receiver clock
  • Determination of unknown GLONASS frequency numbers
  • Baseline selection with advanced conditions regarding GNSS, marginally observed satellites, and beneficial baselines for ambiguity resolution.
  • Automated adjustment of the screening technology for the cycle slip detection and outlier rejection according to the baseline length
  • Automated exclusion of data intervals with exceptionally high number of cycle slips
  • Removal of satellites with unusual high number of data problems
  • Automated detection of misbehaving stations/satellites based on post-fit residuals
Ambiguity resolution
  • Optimized multiple-step ambiguity resolution scheme with different algorithms according to the baseline length, even for very long baselines
  • Self-calibrating ambiguity resolution for GLONASS
  • Consider 1/4-cycle biases resulting from the simultaneous tracking of GPS L2C and L2P signals with some receiver types
  • Re-initialisation of ambiguities resolution results for all or a specific GNSS (if needed)
Processing
  • Double-difference network solution with correct correlations
  • Zero-difference network solution solving for all receiver and satellite clock parameters (equivalent to a consistent double difference solution)
  • Precise Point Positioning (PPP)
  • All three approaches are available for multi- (GPS/GLONASS/...) or single GNSS configurations for single- or dual-frequency datasets
  • Numerous parameter types can be setup at the same time; generation of normal equations without inversion
  • Flexible observation sampling, in particular for epoch parameters
Normal equation handling
  • Geodetic datum definition
  • Efficient parameter transformation for various purposes (reduce the resolution of parameters in time; long-arc for orbit determination)
  • Flexible management to select parameters for pre-elimination or deletion (e.g., exclusion of boundaries of the normal equation to guarantee continuity or keep station dependent parameters for specific sites for collocation)
  • Manipulations of normal equations without inversion
  • Adaption of a priori values for most of the parameters
  • Some parameters can be added to existing normal equations
  • SINEX generation based on "normal equation" or "covariance" representation
  • Computation of repeatability for parameters of the input normal equations
  • Evaluation of the time series by program FODITS (Find Outliers and Discontinuities in Time Series, see PhD thesis Ostini, 2012)
Antennas
  • Import of antenna phase center corrections from ANTEX format
  • Receiver and satellite phase center corrections can be considered for each frequency to be processed
  • Individual GNSS-specific as well as receiver antenna corrections can be introduced
  • Receiver and satellite antenna phase center parameters can be estimated
Orbit modeling and estimation
  • Satellite information file with the complete constellation history
  • Satellite orbits import from precise orbit files depending on the accuracy code
  • Estimation of six initial orbital elements and a set of up to nine dynamical orbit parameters in different frames:
    • Sun-oriented frame at the satellite center of mass
    • Flight direction oriented frame at the satellite center of mass
  • All coefficients of the a priori CODE radiation pressure model are listed in the "Satellite information" file
  • Estimation of stochastic pulses during the orbit integration based on precise orbit files
  • Estimation of stochastic pulses or empirical accelerations from GNSS observation data during the orbit improvement
  • Detection and determination of GPS repositioning events
Differential Code Biases (DCB)
  • Support of P1−C1, P2−C2, and P1−P2 differential code biases
  • Management of inter-system (e.g, between GPS and GLONASS) and inter-frequency (e.g., for GLONASS) code biases
  • Estimation of differential code biases during parameter estimation (ionosphere or clock product generation, Melbourne-Wübbena linear combination) or directly starting from RINEX observation files
Clock product generation
  • Combination of clock RINEX files
  • Automated selection of a reference clock
  • Extrapolation of series from clock RINEX file
  • Phase-based interpolation of clock corrections to generate high-rate clock products
Simulation of GNSS observations
  • According to a given geometry (satellite orbits and station positions) GNSS observations can be computed
  • Assumptions with respect to the noise level, receiver/satellite clocks, ionosphere, troposphere, and cycle slips can be introduced
  • These synthetic data can be processed on zero-difference or double-difference level
  • The correct integer ambiguity is known to be zero in case of ambiguity resolution tests