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Auteur Zhen Shi |
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Adjustment options for a survey network with magnetic levitation gyro data in an immersed under-sea tunnel / Ji Ma in Survey review, vol 51 n° 367 (July 2019)
[article]
Titre : Adjustment options for a survey network with magnetic levitation gyro data in an immersed under-sea tunnel Type de document : Article/Communication Auteurs : Ji Ma, Auteur ; Zhiqiang Yang, Auteur ; Zhen Shi, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 373 - 386 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Topographie
[Termes IGN] compensation de coordonnées
[Termes IGN] gyroscope
[Termes IGN] lever souterrain
[Termes IGN] réseau géodésique spécifique
[Termes IGN] tunnelRésumé : (Auteur) Since gyro azimuths are affected by the complex environmental factors that are present in underground spaces, the adjustment model should take this into account. In general, gyro azimuths are considered to be errorless or equal precision observations in the adjustment model, which leads to the overestimation or underestimation of the weight of the gyro azimuths. To improve the precision of underground networks, measured with a magnetic levitation gyroscope, an adjustment for the survey network with individually weighted gyro observations is proposed. The proposed method was tested on an equivalent mock-up network of the tunnels associated with the Hong Kong-Zhuhai-Macau Bridge. The lateral breakthrough error and lateral standard deviation at the breakthrough point were calculated and compared. Our result shows that the lateral breakthrough error was 4.8 mm with the precision change ratio of 64.5% which suggested that the proposed method is able to improve the precision of the breakthrough point. Numéro de notice : A2019-365 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2018.1563376 Date de publication en ligne : 03/01/2019 En ligne : https://doi.org/10.1080/00396265.2018.1563376 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93454
in Survey review > vol 51 n° 367 (July 2019) . - pp 373 - 386[article]