Filter: This dropdown menu defines which parameter adjustment method is used. ‘Iterated Extended Kalman Filter’ (IEKF) uses an Extended Kalman filter iterating within each epoch, implemented in information form. Usually, this approach leads to the best results due to the necessary linearization of the observation equations. On the other hand, ‘Kalman Filter’ uses a standard Kalman Filter, implemented using the Gain Matrix. Both approaches perform equally well for high-rate data, but IEKF might perform better for 30-second data, for example. Finally, ‘No Filter’ uses a standard Least-Squares Adjustment (e.g., no information is taken to the next epoch). Therefore, all parameters are estimated independently in each epoch and the highly precise phase measurements are not used to constrain the float ambiguities.
Default settings: Load the default settings for the currently selected filter. This option will overwrite all current values on the whole panel.
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'Forwards' runs the filter in the direction of time, from the first to the last defined epoch (see the 'Processing Options' panel). This is the default option and the usual approach in PPP, which is capable of operating in real time. The other three options are more experimental and suitable for post-processing only: 'Fwd-Bwd' runs from the first epoch to the last, and then back again. 'Bwd-Fwd' runs from the last epoch to the first, and then forwards. 'Backwards' runs from the last epoch to the first. Please note that 'Fwd-Bwd' and 'Bwd-Fwd' smooth out the convergence period and the processing time is roughly doubled.
Inital Std: A priori variance of this parameter. This is used to initialize the covariance matrix of the parameters in the 1st epoch of processing.
System Noise: The system system noise used to create the Noise Matrix and defines how much uncertainty is in this parameter from one epoch. Please note that the defined hourly system noise is scaled by the observation interval during processing.
Dynamic Model: Used to create the transition matrix (which is done each epoch). How the parameter behaves from one epoch to another.
Estimate: Enable this checkbox to estimate the receiver differential code biases during the PPP calculations. It depends on the chosen PPP model if this is necessary and useful.
Save: Save the current values from the filter settings into a *.mat-file.
Load: Load already saved values from the filter settings from a *.mat-file.
Enable this option if your GNSS receiver is placed on a satellite (e.g., LEO satellite) to improve the PPP solution using dynamic models for position and velocity estimation. You will need to define the mass [kg], area [m²], drag coefficient [] and solar coefficient [] of the satellite.
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