Centre de documentation
scientifique

Stochastic modeling for VRS network-based GNSS RTK with residual interpolation uncertainty / Thanate Jongrujinan in Journal of applied geodesy, vol 14 n° 3 (July 2020)  

Public [article]  inJournal of applied geodesy > vol 14 n° 3 (July 2020) . - pp 317 – 325 Titre : Stochastic modeling for VRS network-based GNSS RTK with residual interpolation uncertainty Type de document : Article/Communication Auteurs : Thanate Jongrujinan, Auteur ; Chalermchon Satirapod, Auteur Année de publication : 2020 Article en page(s) : pp 317 – 325 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] correction atmosphérique [Termes IGN] incertitude de position [Termes IGN] interpolation [Termes IGN] matrice de covariance [Termes IGN] modèle stochastique [Termes IGN] positionnement cinématique en temps réel [Termes IGN] positionnement par GNSS [Termes IGN] précision du positionnement [Termes IGN] résolution d'ambiguïté [Termes IGN] station virtuelle de référence [Vedettes matières IGN] Traitement de données GNSS Résumé : (auteur) The key concept of the virtual reference station (VRS) network-based technique is to use the observables of multiple reference stations to generate the network corrections in the form of a virtual reference station at a nearby user’s location. Regarding the expected positioning accuracy, the novice GNSS data processing strategies have been adopted in the server-side functional model for mitigating distance-dependent errors including atmospheric effects and orbital uncertainty in order to generate high-quality virtual reference stations. In addition, the realistic stochastic model also plays an important role to take account of the unmodelled error in the rover-side processing. The results of our previous study revealed that the minimum norm quadratic unbiased estimation (MINQUE) stochastic model procedure can improve baseline component accuracy and integer ambiguity reliability, however, it requires adequate epoch length in a solution to calculate the elements of the variance-covariance matrix. As a result, it may not be suitable for urban environment where the satellite signal interruptions take place frequently, therefore, the ambiguity resolution needs to be resolved within the limited epochs. In order to address this limitation, this study proposed the stochastic model based on using the residual interpolation uncertainty (RIU) as the weighting schemes. This indicator reflects the quality of network corrections for any satellite pair at a specific rover position and can be calculated on the epoch-by-epoch basis. The comparison results with the standard stochastic model indicated that the RIU-weight model produced slightly better positioning accuracy but increased significant level of the ambiguity resolution successful rate. Numéro de notice : A2020-398 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1515/jag-2020-0007 Date de publication en ligne : 10/04/2020 En ligne : https://doi.org/10.1515/jag-2020-0007 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95433 [article]