Boosting Research for Carbon Neutral on Edge UWB Nodes Integration Communication Localization Technology of IoV

被引:2
|
作者
Huang, Ouhan [1 ,2 ]
Rao, Huanle [3 ]
Zhang, Zhongyi [1 ]
Gu, Renshu [1 ]
Xu, Hong [4 ]
Jia, Gangyong [1 ]
机构
[1] Hangzhou Dianzi Univ, Sch Comp Sci & Technol, Hangzhou 310005, Peoples R China
[2] Fudan Univ, Key Lab Informat Sci Electromagnet Waves, MoE, Shanghai 200437, Peoples R China
[3] Hangzhou Dianzi Univ, Sch Automat, Hangzhou 310005, Peoples R China
[4] China Elect Technol Grp Corp CETC, Res Inst 32, Shanghai 200231, Peoples R China
来源
基金
中国国家自然科学基金;
关键词
Industrial Internet of Things; Internet of Vehicles; carbon neutrality; ultra-bandwidth; weighted least squares; extended kalman filter; NAVIGATION; SYSTEM; INTERNET; 5G; ARCHITECTURE; CHALLENGES; NETWORKS; SENSORS; VISION; FUSION;
D O I
10.1109/TSUSC.2023.3266729
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Reducing carbon emission to improving the economy of fuel vehicle is one of the effective ways to achieve Carbon Neutrality. The Internet of Vehicles (IoV) is a developing technology for deep integration of the Internet of Things (IoT) and transportation. The Industrial Internet of Things (IIoT) can incorporate vehicle information to pinpoint vehicle carbon emissions and provide a foundation for the subsequent carbon-neutral decision-making process. To achieve the precision needs of IoT, however, more than conventional Global Navigation Satellite Systems (GNSS) are required. To achieve carbon emission detection, provide high-precision positioning, and provide a foundation for subsequent carbon-neutral decision-making, it is essential to design a carbon emission detection and positioning system with the capability of vehicle networking. The geographic proximity of edge Ultra Wide Band (UWB) nodes and the merging of various data sources are two methods we suggest employing in this study to increase location accuracy in IIoT situations. After carefully examining the positioning error of the single-edge node and the range error achieved in the UWB communication system, we choose a suitable filtering strategy to enhance single-node accuracy. Following the improvement of single-node accuracy, we fuse the location information of multiple edge nodes using a Weighted Least Squares algorithm in the spatial dimension; in the temporal dimension, we use Extended Kalman filtering to fuse the data over a period of time due to the temporal correlation of inter-node communication. Experimental results demonstrate that our co-localization method, which combines temporal and spatial information, achieves higher localization accuracy in comparison with previous work.
引用
收藏
页码:341 / 353
页数:13
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