This paper adapts and discusses the information criterion (IC) approach for the validation of baseline GNSS observation models in the context of outliers. Three IC methods are compared with the conventional procedure of iterative data snooping (IDS). To verify the reliability of the two considered approaches, several scenarios differing in: the magnitude and number of outliers, and the interval between measurement epochs were investigated. Generally, the IDS procedure achieved the highest rates of correct model specification when no outlier existed. However, as the number of outliers was increasing one of the IC methods was starting to achieve the highest rates.

The information criterion approach improves the validation of GNSS observation models when outliers are present, but iterative data snooping remains the most reliable method when no outliers exist.

Validation of GNSS baseline observation models using information criteria

Key Takeaway: The information criterion approach improves the validation of GNSS observation models when outliers are present, but iterative data snooping remains the most reliable method when no outliers exist.