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Does RAIM with Correct Exclusion Produce Unbiased Positions?
As the navigation solution of exclusion-based RAIM follows from a combination of least-squares estimation and a statistically based exclusion-process, the computation of the integrity of the navigation solution has to take the propagated uncertainty of the combined estimation-testing procedure into...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5539570/ https://www.ncbi.nlm.nih.gov/pubmed/28672862 http://dx.doi.org/10.3390/s17071508 |
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author | Teunissen, Peter J. G. Imparato, Davide Tiberius, Christian C. J. M. |
author_facet | Teunissen, Peter J. G. Imparato, Davide Tiberius, Christian C. J. M. |
author_sort | Teunissen, Peter J. G. |
collection | PubMed |
description | As the navigation solution of exclusion-based RAIM follows from a combination of least-squares estimation and a statistically based exclusion-process, the computation of the integrity of the navigation solution has to take the propagated uncertainty of the combined estimation-testing procedure into account. In this contribution, we analyse, theoretically as well as empirically, the effect that this combination has on the first statistical moment, i.e., the mean, of the computed navigation solution. It will be shown, although statistical testing is intended to remove biases from the data, that biases will always remain under the alternative hypothesis, even when the correct alternative hypothesis is properly identified. The a posteriori exclusion of a biased satellite range from the position solution will therefore never remove the bias in the position solution completely. |
format | Online Article Text |
id | pubmed-5539570 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-55395702017-08-11 Does RAIM with Correct Exclusion Produce Unbiased Positions? Teunissen, Peter J. G. Imparato, Davide Tiberius, Christian C. J. M. Sensors (Basel) Article As the navigation solution of exclusion-based RAIM follows from a combination of least-squares estimation and a statistically based exclusion-process, the computation of the integrity of the navigation solution has to take the propagated uncertainty of the combined estimation-testing procedure into account. In this contribution, we analyse, theoretically as well as empirically, the effect that this combination has on the first statistical moment, i.e., the mean, of the computed navigation solution. It will be shown, although statistical testing is intended to remove biases from the data, that biases will always remain under the alternative hypothesis, even when the correct alternative hypothesis is properly identified. The a posteriori exclusion of a biased satellite range from the position solution will therefore never remove the bias in the position solution completely. MDPI 2017-06-26 /pmc/articles/PMC5539570/ /pubmed/28672862 http://dx.doi.org/10.3390/s17071508 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Teunissen, Peter J. G. Imparato, Davide Tiberius, Christian C. J. M. Does RAIM with Correct Exclusion Produce Unbiased Positions? |
title | Does RAIM with Correct Exclusion Produce Unbiased Positions? |
title_full | Does RAIM with Correct Exclusion Produce Unbiased Positions? |
title_fullStr | Does RAIM with Correct Exclusion Produce Unbiased Positions? |
title_full_unstemmed | Does RAIM with Correct Exclusion Produce Unbiased Positions? |
title_short | Does RAIM with Correct Exclusion Produce Unbiased Positions? |
title_sort | does raim with correct exclusion produce unbiased positions? |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5539570/ https://www.ncbi.nlm.nih.gov/pubmed/28672862 http://dx.doi.org/10.3390/s17071508 |
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