Skip to Main content Skip to Navigation
Journal articles

Multilateration with Self-Calibration: Uncertainty Assessment, Experimental Measurements and Monte-Carlo Simulations

Abstract : Large-volume metrology is essential to many high-value industries and contributes to the factories of the future. In this context, we have developed a tri-dimensional coordinate measurement system based on a multilateration technique with self-calibration. In practice, an absolute distance meter, traceable to the SI metre, is shared between four measurement heads by fibre-optic links. From these stations, multiple distance measurements of several target positions are then performed to, at the end, determine the coordinates of these targets. The uncertainty on these distance measurements has been determined with a consistent metrological approach and it is better than 5 µm. However, the propagation of this uncertainty into the measured positions is not a trivial task. In this paper, an analytical solution for the uncertainty assessment of the positions of both targets and heads under a multilateration scenario with self-calibration is provided. The proposed solution is then compared to Monte-Carlo simulations and to experimental measurements: it follows that all three approaches are well agreed, which suggests that the proposed analytical model is accurate. The confidence ellipsoids provided by the analytical solution described well the geometry of the errors.
Complete list of metadata

https://hal-cnam.archives-ouvertes.fr/hal-03670747
Contributor : Marie-Liesse Bertram Connect in order to contact the contributor
Submitted on : Tuesday, May 17, 2022 - 4:38:54 PM
Last modification on : Saturday, May 21, 2022 - 3:24:43 AM

File

metrology-02-00015-v3.pdf
Publisher files allowed on an open archive

Licence


Distributed under a Creative Commons Attribution 4.0 International License

Identifiers

Collections

Citation

Joffray Guillory, Daniel Truong, Jean-Pierre Wallerand. Multilateration with Self-Calibration: Uncertainty Assessment, Experimental Measurements and Monte-Carlo Simulations. Metrology, MDPI, 2022, 2 (2), pp.241 - 262. ⟨10.3390/metrology2020015⟩. ⟨hal-03670747⟩

Share

Metrics

Record views

5

Files downloads

1