.png){kind=icon}
返回
Node Dynamic Localization and Prediction Algorithm for Internet of Underwater Things
.png){kind=icon}
PRE
AI
DOI：10.1109/JIOT.2021.3108424.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This article investigates the underwater node dynamic localization and prediction problems in a dynamic sensor network. Node localization in the Internet of underwater things is the basis of target tracking and ocean monitoring. At present, most of the node location algorithms assume calm sea and fixed node location. However, the current velocity is uncertain in space and time. The nodes are drifted with the current motion. Therefore, most of the localization algorithms lose efficacy in the actual marine environment. In order to solve the above problems, a node dynamic prediction algorithm is proposed. First, the node mobility model is improved, which is more suitable for the actual marine environment. Second, a frequency-based anchor node prediction algorithm is designed to improve anchor node location accuracy. Third, when the ordinary node receives the signals sent by anchor nodes of different depths, a deep information-based weighted fusion method is designed for the ordinary node localization in order to mine more information in each direction. Finally, location and prediction simulation in sensor networks is carried out. The results show that the proposed node localization and prediction algorithm is more accurate than SMLP and high-precision localization with mobility prediction algorithms and prove the enhanced effect of our method in dynamic marine.
Keyword:
Location awareness
Prediction algorithms
Heuristic algorithms
Sea surface
Robot sensing systems
Oceans
Kinematics
Dynamic information fusion
improved node mobility model
Internet of Underwater Things (IoUT)
mobile node
node localization and prediction
期刊
IF:
8.9
论文数:
1.4W
被引数:
7.8W
机构
引用论文
A Node Self-Localization Algorithm With a Mobile Anchor Node in Underwater Acoustic Sensor Networks基于移动锚节点的水声传感器网络节点自定位算法.png)
IEEE ACCESS
OAAI
IEEE ACCESSIF3.6
OAAI分享收藏Impact of Clinical and Socio-Demographic Factors on the Quality of Life in Romanian People with EpilepsyHealthcareOAAI
HealthcareIF0
OAAI分享收藏分享收藏AUV-Aided Localization for Internet of Underwater Things: A Reinforcement-Learning-Based Method
PREAI
分享收藏
查看更多内容