Investigation of wireless tracking performance in the tunnel-like environment with particle filter
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
When the basic nonlinear filtering problem for dynamic systems is considered, in such case, the particle filter is one of the suitable methods that has perhaps become one of the most commonly used methods in recent years. Positioning or localization falls under such a nonlinear filtering problem. Positioning is a matter of interest for both domestic and industrial application, due to its potential use in wide range of context-aware services that it can enable by leveraging the Internet of Things approach. However, in areas where GPS signals are not available such as underground tunnel roadways, where the localization is done mostly using radio beacons. This study mathematically simulates tracking operation in such a tunnel-like situation and studied the position estimation by the particle filter. From the results, we were able to visualize how varying different configuration parameters affect the estimation accuracies and also get an idea of worst-case estimates by seeing its standard deviation of estimated positions for different instances of repeated experiments. And our results also confirmed that deploying additional beacons have a contribution to the improvement in error tolerance. However, the improvements are significantly notable only around the point where beacon has been added. When the basic nonlinear filtering problem for dynamic systems is considered, in such case, the particle filter is one of the suitable methods that has perhaps become one of the most commonly used methods in recent years. Positioning or localization falls under such a nonlinear filtering problem. Positioning is a matter of interest for both domestic and industrial application, due to its potential use in wide range of context-aware services that it can enable by leveraging the Internet of Things approach. However, in areas where GPS signals are not available such as underground tunnel roadways, where the localization is done mostly using radio beacons. This study mathematically simulates tracking operation in such a tunnel-like situation and studied the position estimation by the particle filter. From the results, we were able to visualize how varying different configuration parameters affect the estimation accuracies and also get an idea of worst-case estimates by seeing its standard deviation of estimated positions for different instances of repeated experiments. And our results also confirmed that deploying additional beacons have a contribution to the improvement in error tolerance. However, the improvements are significantly notable only around the point where beacon has been added.
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.
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 découle