Localization technology of underwater acoustic wireless network based on array signal processing
Notice bibliographique
Résumé
In the area of large wireless sensor networks (WSNs), localization is important for many applications. In the WSNs, some nodes can localize themselves, which are called anchor nodes. A traditional method called three dimensional underwater localization (3DUL) is to deploy buoys equipped with GPS receivers on the surface of the sea. Sensors can estimate their distances to the anchors using the location information of anchors. This method is quite straightforward but not economical for large-scale WSNs, suffering from limitations such as time consumption and low coverage. In certain circumstances, this method becomes infeasible. In order to overcome the above-mentioned problems involved in the fixedreference method, localization systems using mobile anchors have been developed. In the underwater environment, autonomous underwater vehicles (AUVs) are good choices of mobile anchors. An AUV can be set to move along a predefined trajectory and broadcast its location information to underwater sensor nodes through acoustic signals. After receiving the location information, sensor nodes can localize themselves. The key advantage of this method is that the costs for deploying such sensor networks remain relatively low, even though a large number of anchors is used or the area of interest are extended. A hydrophone is a device that can receive underwater acoustic signals. In the application of underwater localization, multiple hydrophones can be arranged in an array to improve localization accuracy. Hydrophone can be divided into three types: (1) long baseline system (LBL), (2) short baseline system (SBL), (3) ultra short baseline system (USBL). Furthermore, a hydrophone array can be loaded on an AUV to create a big virtual array, which is the principle of synthetic aperture sonar (SAS). The advantage of SAS is that it can optimize the tradeoffs between sonar array length and range scale.Motivated by these ideas, this thesis work has investigated AUV-aided localization systems using three kinds of hydrophone arrays: (1) a Doppler localization system with a single hydrophone, (2) a towed uniform linear array (ULA) based localization system with a new structure, (3) underwater localization system assisted by a moving uniform circular array (UCA). Detailed challenges in underwater localization and solutions to them are presented. System models are established and verified based on simulation results. It has been demonstrated that localization accuracy can be improved dramatically by using hydrophone arrays. In the first application, Doppler-based localization method has been found to perform better than time of arrival (ToA) and time difference of arrival (TDoA) methods. In order to increase localization accuracy, a new structure of towed sonar array has been proposed and it can be useful for localizing an underwater object. Associated with improved localization accuracy, the computational complexity can be lowered. Because UCA gives a 360○ azimuth coverage, it can be mounted on an AUV to achieve the task of localizing an underwater object. The accuracy of this method can be higher than the ULA method, but the computational complexity increases as well.
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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».