版权说明 操作指南
首页 > 成果 > 详情

Spatiotemporal optimization for communication-navigation-sensing collaborated emergency monitoring

认领
导出
Link by DOI
反馈
分享
QQ微信 微博
成果类型:
期刊论文
作者:
Tan, Xicheng;Liu, Bocai;Li, Chaopeng;Hussain, Zeenat Khadim;Wang, Kaiqi;...
通讯作者:
Tan, XC
作者机构:
[Tan, Xicheng; Hussain, Zeenat Khadim; Mei, Zhiyuan; Yang, Danyang; Li, Chaopeng; Liu, Bocai; Ye, Mengyan; Wang, Kai] Wuhan Univ, Sch Remote Sensing & Informat Engn, 129 Luoyu Rd, Wuhan, 430079, Peoples R China.
[Wang, Kaiqi] Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan, Peoples R China.
通讯机构:
[Tan, XC ] W
Wuhan Univ, Sch Remote Sensing & Informat Engn, 129 Luoyu Rd, Wuhan, 430079, Peoples R 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:
National Natural Science Foundation of China (NSFC) [42271425, 41871312]
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...

反馈

验证码:
看不清楚,换一个
确定
取消

成果认领

标题:
用户 作者 通讯作者
请选择
请选择
确定
取消

提示

该栏目需要登录且有访问权限才可以访问

如果您有访问权限,请直接 登录访问

如果您没有访问权限,请联系管理员申请开通

管理员联系邮箱:yun@hnwdkj.com