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Spatiotemporal optimization for communication-navigation-sensing collaborated emergency monitoring

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成果类型:
期刊论文
作者:
Xicheng Tan*;Bocai Liu;Chaopeng Li;Zeenat Khadim Hussain;Kaiqi Wang;...
通讯作者:
Xicheng Tan
作者机构:
[Xicheng Tan; Bocai Liu; Chaopeng Li; Zeenat Khadim Hussain; Kai Wang; Mengyan Ye; Danyang Yang; Zhiyuan Mei] School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, People’s Republic of China
[Kaiqi Wang] School of Mathematics and Computer Science, Wuhan Polytechnic University, Wuhan, People’s Republic of China
通讯机构:
[Xicheng Tan] S
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, People’s Republic of China
语种:
英文
关键词:
Spatiotemporal optimization;deep reinforcement learning;GeoAI;emergency response
期刊:
国际数字地球学报(英文)
ISSN:
1753-8947
年:
2025
卷:
18
期:
1
基金类别:
Funding
机构署名:
本校为其他机构
院系归属:
数学与计算机学院
摘要:
In the event of disaster-related disruptions to public networks, an air-ground communication-navigation-sensing (CNS) ad-hoc network (ANET) can effectively support emergency response operations by ensuring communication, navigation and sensing capabilities. However, during extreme events such as typhoons and torrential rain, flight operations become impossible for aircraft. Therefore, a critical issue that requires immediate investigation is how to effectively provide communication, navigation, and sensing assistance to emergency regions using only ground-based CNS nodes. This paper presents a...

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