Three-dimensional outlier detection for GPS networks and their densification via the BLIMPBE approach

This article discusses outlier detection based on Baarda's theory, but applied to three-dimensional GPS baseline vectors, as compared to the traditional approach of investigating the vector components individually (one-dimensional). In addition, Schaffrin's recently proposed estimator of type BLIMPBE is discussed and contrasted with a minimum constrained least-squares adjustment, specifically Partial-MINOLESS. A more detailed discussion of these topics, which includes additional formulas and derivations, can be found in the first author's Master of Science thesis, hereinafter referred to as Report 465.