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

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Abstract

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.

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References

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Authors and Affiliations

  1. Dept. of Civil and Environmental Engineering and Geodetic Science, The Ohio State University, 2070 Neil Ave., Columbus, OH , 43210-1275, USA

    Kyle B. Snow & Burkhard Schaffrin

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  1. Kyle B. Snow
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  2. Burkhard Schaffrin
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Correspondence to Kyle B. Snow.

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Snow, K.B., Schaffrin, B. Three-dimensional outlier detection for GPS networks and their densification via the BLIMPBE approach. GPS Solutions 7, 130–139 (2003). https://doi.org/10.1007/s10291-003-0058-2

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  • DOI: https://doi.org/10.1007/s10291-003-0058-2

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