Filter: This dropdown menu defines which parameter adjustment method is used. ‘Kalman Filter iterative’ uses a Kalman filter iterating within each epoch. 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. This approach might be a sensible alternative, especially when processing high-rate data. Finally, ‘No Filter’ uses a standard Least-Squares Adjustment (e.g., no information is taken to the next epoch). Therefore, all parameters are independently estimated in each epoch, and no advantage is taken from the highly precise phase measurements because there is no constraint on 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.
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: used to create the Noise Matrix (which is done each epoch). How much uncertainty is in this parameter from one epoch to the other added to .param_sigma
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.
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