- 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

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

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