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Evaluation of Compatibility among Network Adjustment Software: CoMeT, LGC, and Trinet+
A network adjustment program is an essential tool for surveyors. It allows the computation of point coordinates and confidence regions from measurements undertaken in the field. It also helps surveyors in the design of optimal networks, both in terms of accuracy and reliability. Conservatoire nation...
Autores principales: | , , , , , |
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Lenguaje: | eng |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1061/(asce)su.1943-5428.0000304 http://cds.cern.ch/record/2801423 |
Sumario: | A network adjustment program is an essential tool for surveyors. It allows the computation of point coordinates and confidence regions from measurements undertaken in the field. It also helps surveyors in the design of optimal networks, both in terms of accuracy and reliability. Conservatoire national des arts et métiers (Cnam), European Organization for Nuclear Research (CERN), and School of Management and Engineering Vaud (HEIG-VD) are three institutions that have developed their own network adjustment applications: Compensation de Mesures Topographiques (CoMeT), Logiciel Général de Compensation (LGC), and Trinet+, respectively. In all these applications, three-dimensional (3D) mathematical functional models are used to process conventional observations and global navigation satellite system (GNSS) 3D vectors. However, some discrepancies may exist in the obtained results between these applications due to differences in the implementation of the functional models. The main objective of this work is to study software effects, and to ensure compatibility and interoperability between these three network adjustment applications. We first present the relevant differences between these applications and then the processing methodology adopted to ensure the best compatibility and interoperability between them. Using generated measurements, which include Gaussian errors, we have been able to study the impact of any differences in the implementation of the functional models on the estimated variance factor and adjusted parameters. |
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