Integration of precise point positioning and reduced inertial sensors system
Notice bibliographique
Résumé
In Global Positioning System (GPS), Precise Point Positioning (PPP) achieves the highest accuracy in point positioning. It approaches centimetre-level accuracy in static mode and sub-decimetre accuracy in kinematic mode. PPP is an alternative approach to carrier-phase-based Differential GPS (DGPS) and offers advantages over DGPS. PPP uses GPS observations from a single receiver for position estimation, which is simpler than using more than one GPS receiver. However, PPP needs rigorous modelling for all errors and biases, which are otherwise cancelled out or mitigated when using DGPS. PPP’s popularity is on the rise, as it is ideal for land-vehicle positioning and navigation. However, in challenging environments, PPP suffers from a signal loss that prevent continuous navigation or a reduction in the number of visible satellites that causes accuracy degradation. This research integrates PPP with a Reduced Inertial Sensors System (RISS) — a low-cost system that uses data from reduced MEMS-based inertial sensors and vehicle odometry — to provide accurate and inexpensive land-vehicle navigation systems. The system is integrated in a tightly coupled mode through the use of an Extended Kalman Filter (EKF), which employs an improved error model for the RISS data. The system was tested using data from real driving routes with single-frequency code-based PPP/RISS (SF-code-PPP/RISS), dual-frequency code-based PPP (DF-code-PPP/RISS), smoothed dual-frequency code-based PPP (S-DF-code-PPP/RISS), and code- and carrier-phase-based PPP (code-carrier-PPP/RISS). The performance of the developed PPP/RISS was evaluated using position RMS and maximum errors during continuous GPS availability as well as during signal outages. The developed integrated algorithms were assessed using three real road tests that capture different navigational conditions. The results show that when five or more satellites are available, code-carrier-PPP/RISS solution is superior to that of SF- and DF-code-PP/RISS. For latitude, code-carrier-PPP/RISS solution was 47% and 20% more precise than the SF- and DF-code- PP/RISS counterparts, respectively. For longitude, code-carrier-PPP/RISS solution was 65% and 31% more precise than the SF- and DF-Code-PP/RISS counterparts, respectively. Similarly, the altitude solution was improved by 46% and 25%, respectively. During GPS signal outages of 60 seconds, code-carrier-PPP/RISS’s algorithms outperformed that of SF- and DF-code-PPP/RISS by about 35% when the satellite availability level was set to three satellites. For other satellite availability levels, the algorithms performed almost identically.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».