Deep Learning Based Localization Scheme for UAV Aided Wireless Sensor Networks

被引：0

作者：

Zhang, Hanjun ^{[1
]}

Yan, Feng ^{[1
,2
]}

Li, Hao ^{[2
]}

Ding, Kai ^{[2
]}

Wu, Tao ^{[3
]}

Xia, Weiwei ^{[1
]}

Shen, Lianfeng ^{[1
]}

机构：

[1] Southeast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Peoples R China

[2] Sci & Technol Near Surface Detect Lab, Wuxi 214035, Peoples R China

[3] Jiangsu ZhongLi Elect Informat Sci Tech Co Ltd, Changshu 215542, Peoples R China

来源：

2022 14TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS AND SIGNAL PROCESSING, WCSP | 2022年

关键词：

UAV; WSN; deep learning; CNN; localization;

D O I：

10.1109/WCSP55476.2022.10039418

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, a deep learning based localization scheme is proposed for unmanned aerial vehicle (UAV) aided wireless sensor networks (WSNs). The scheme contains two components which are ranging and localization. In the ranging component, a UAV works as a data collector and calculates the distances between the ground sensor nodes. In the localization component, a localization convolutional neural network (CNN) is built and trained to estimate the nodes coordinates using the ranging information. Simulations results show that the proposed localization scheme has a higher accuracy comparing with a related method.

引用

页码：638 / 643

页数：6

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