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基于旋翼无人机近地面空间应急物联网节点动态协同部署

王巍 彭力 赵继军 朱天宇 崔益豪 田立勤

王巍, 彭力, 赵继军, 朱天宇, 崔益豪, 田立勤. 基于旋翼无人机近地面空间应急物联网节点动态协同部署. 自动化学报, 2021, 47 (8): 2002−2015 doi: 10.16383/j.aas.c180146
引用本文: 王巍, 彭力, 赵继军, 朱天宇, 崔益豪, 田立勤. 基于旋翼无人机近地面空间应急物联网节点动态协同部署. 自动化学报, 2021, 47 (8): 2002−2015 doi: 10.16383/j.aas.c180146
Wang Wei, Peng Li, Zhao Ji-Jun, Zhu Tian-Yu, Cui Yi-Hao, Tian Li-Qin. Dynamic cooperative deployment of emergency internet of things near ground space based on drone. Acta Automatica Sinica, 2021, 47 (8): 2002−2015 doi: 10.16383/j.aas.c180146
Citation: Wang Wei, Peng Li, Zhao Ji-Jun, Zhu Tian-Yu, Cui Yi-Hao, Tian Li-Qin. Dynamic cooperative deployment of emergency internet of things near ground space based on drone. Acta Automatica Sinica, 2021, 47 (8): 2002−2015 doi: 10.16383/j.aas.c180146

基于旋翼无人机近地面空间应急物联网节点动态协同部署

doi: 10.16383/j.aas.c180146
基金项目: 

国家重点研发计划 2018YFF0301004

国家重点研发计划 2018YFD0400902

国家自然科学基金 61802107

国家自然科学基金 61873112

教育部–中国移动科研基金 MCM20170204

河北省自然科学基金 F2015402108

河北省物联网数据采集与处理工程技术研究中心开放课题 2016-2

江苏省博士后科研资助计划项目 1601085C

详细信息
    作者简介:

    彭力    江南大学教授. 2002年获得北京科技大学控制理论与控制工程博士学位. 主要研究方向为视觉物联网.E-mail: pengli@jiangnan.edu.cn

    赵继军    河北工程大学教授. 2003年获得北京邮电大学电磁场与微波技术博士学位. 主要研究方向为宽带通信网, 传感网与物联网.E-mail: zjijun@hebeu.edu.cn

    朱天宇   河北工程大学信息与电气工程学院硕士研究生.主要研究方向为无人机, SLAM.E-mail: zihan126410@sina.com

    崔益豪   河北工程大学信息与电气工程学院硕士研究生.主要研究方向为物联网监测系统.E-mail: yihaocui1994@163.com

    田立勤   华北科技学院教授. 2009年获得北京科技大学计算机应用技术博士学位.主要研究方向为物联网远程信息监控、网络用户行为认证.E-mail: tianliqin@ncist.edu.cn

    通讯作者:

    王巍    河北工程大学副教授. 2012年获得北京科技大学信息工程学院控制科学与工程博士学位. 主要研究方向为公共安全物联网, 隐式人机交互. 本文通信作者.E-mail: wangwei83@hebeu.edu.cn

  • 本文责任编委 陈积明

Dynamic Cooperative Deployment of Emergency Internet of Things Near Ground Space Based on Drone

Funds: 

National Key Research and Development Program of China 2018YFF0301004

National Key Research and Development Program of China 2018YFD0400902

National Natural Science Foundation of China 61802107

National Natural Science Foundation of China 61873112

Education Ministry and China Mobile Science Research Foundation MCM20170204

Natural Science Foundation of Hebei Province of China F2015402108

Foundation of Internet of Things Data Acquisition and Processing Engineering Technology Research Center in Hebei Province 2016-2

Jiangsu Planned Projects for Postdoctoral Research Funds 1601085C

More Information
    Author Bio:

    PENG Li    Professor at Jiangnan University. He received his Ph. D. degree from University of Science & Technology Beijing in 2002. His main research is visual internet of things

    ZHAO Ji-Jun    Professor at Hebei University of Engineering. He received his Ph. D. degreer from Beijing University of Posts and Telecommunications in 2003. His research interest covers broadband communication network, sensor network and internet of things

    ZHU Tian-Yu   Master student at School of Information & Electrical Engineering, Hebei University of Engineering. His research interest covers UAV and SLAM

    CUI Yi-Hao   Master student at School of Information & Electrical Engineering, Hebei University of Engineering. His main research is monitoring system of internet of things

    TIAN Li-Qin   Professor at North China Institute of Science and Technology. He received his Doctor degree from University of Science & Technology Beijing in 2009. His research interest covers remote monitoring of Internet of Things, network user behavior authentication

    Corresponding author: WANG Wei    Associate professor at Hebei University of Engineering. He received his Ph. D. degree from University of Science & Technology Beijing in 2012. His research interest covers public safety internet of things and implicit human-computer interaction. Corresponding author of this paper
  • Recommended by Associate Editor CHEN Ji-Ming
  • 摘要: 针对基于旋翼无人机的近地面空间应急物联网在缺少地面基站和能量受限的情况下, 可靠节能地远距离传输重点区域全信息的要求, 研究由无人机组成的移动Ad-Hoc网络的远距离通信问题, 提出近地面空间应急物联网空地节点动态协同部署方法. 首先, 对该类物联网进行系统建模; 其次, 根据所建模型中无人机编队大范围、队列化、微漂移地分散于监测区域的特点和编队的联合分布情况, 在提供可靠通信的同时, 将系统通信能耗和移动能耗的计算构建成二次约束二次规划问题; 再次, 根据Gerschgorin圆盘定理和根的存在性定理, 证明了此问题为凸优化问题, 进而可求解得到移动地面站的最佳路径点, 实现近地面空间应急物联网空地节点动态协同部署. 最后, 通过实验, 从通信耗能和运动耗能两方面验证了本文所提方法的有效性, 同时, 也分析了影响本文所述方法效能的因素.
    Recommended by Associate Editor CHEN Ji-Ming
    1)  本文责任编委 陈积明
  • 图  1  系统模型

    Fig.  1  System model

    图  2  位置关系

    Fig.  2  Position relationship

    图  3  Drones cube中无人机空基监测平台立体结构

    Fig.  3  The three-dimensional structure of the air based monitoring platform for unmanned aerial vehicle in drones cube

    图  4  不同分布的最佳路径点$(h_{\text{min}} = 160 \text{m})$

    Fig.  4  The optimal path points in different distribution condition $(h_{\text{min}} = 160 \text{m})$

    图  5  三种Drones cube分布下的MES移动距离

    Fig.  5  MES moving distance under three kinds of drones cube distribution

    图  6  不同分布的Drones cube静态通信能量$(H = 160 \text{m})$

    Fig.  6  Static communication energy under different kinds of Drones cube distribution $(H = 160 \text{m})$

    图  7  直线分布Drones cube静态通信能耗纵向不均衡率

    Fig.  7  Vertical disequilibrium rate of energy consumption in Drones cube static communication under linear distribution

    图  8  三种Drones cube分布下的静态通信能耗增长率

    Fig.  8  Energy consumption growth rate of static communication under three kinds of Drones cube distribution

    图  9  直线分布的Drones cube静态通信能耗与HD的关系

    Fig.  9  The relationship between the energy consumption of drones cube static communication and H and D

    图  10  直线分布的Drones cube静态通信能耗拟合

    Fig.  10  Energy consumption fitting of drones cube static communication under linear distribution

    图  11  直线分布的Drones cube动态通信能耗$(H = 150, D = 75)$

    Fig.  11  Dynamic communication energy consumption of drones cube under linear distribution$(H = 150, D = 75)$

    表  1  国内外相关研究

    Table  1  Related works

    文献 内容 网络类型 无人机数量 不足
    [4] 无人机最优部署与移动 D2D通信网络 一个 未研究上行通信
    [5] 无人机最优轨迹 Ad-hoc网络 多个 未研究无人机运动
    [6] 静态地面用户与无人机联合最优部署 IoT (Internet of things) 多个 未研究地面用户的动态问题
    [7] 高效地数据采集与簇头充电方法 WSN (Wireless sensor networks) 多个 只针对静态传感网, 未研究最优部署问题
    [8-9] 节能的上行传输策略 IoT M2M (Machine-to machine)网络 未考虑设备的运动
    [10-11] 过载和中断预防方法 蜂窝网络 多个 未研究无人机覆盖性能
    [12] 无人机最优轨迹 WSN 多个 只针对静态传感设备
    [13-14] 蜂窝网与D2D (Device-to-device)设备共存 蜂窝网络 一个 未研究无人机的覆盖和通信性能
    下载: 导出CSV

    表  2  仿真参数

    Table  2  Simulation parameters

    参数 描述
    $f_{c}$ 载波频率 $\text{2 GHz}$
    $v_{\cdot}^{t}$ 地面移动中继的速度 $\text{3.6 km/h}$
    $E$ 各簇旋翼无人机用于通信总能量 $\text{3 J}$
    $\delta$ 误码率要求 $10^{-8}$
    $\varepsilon$ 视距通信概率要求 0.95
    $N_{\text{o}}$ 噪声功率谱密度 $-170$ dBm/Hz
    $R_{\text{b}}$ 数据传输速率 $\text{200 kbps}$
    $B$ 传输带宽 $\text{200 kHz}$
    $\eta$ 附加路径损耗 $\text{5 dB}$
    $\psi$ 环境参数1 11.95
    $\beta$ 环境参数2 0.14
    下载: 导出CSV

    表  3  旋翼无人机数量与算法运行时长

    Table  3  Number of drones and algorithm running 09:39:56

    分布形式 数量$K$ 算法运行时长$(\text{s})$ 平均时长$(\text{s})$
    第1次 第2次 第3次 第4次 第5次
    直线 96 10.773 10.722 10.683 10.731 10.689 10.719
    108 10.788 10.753 10.761 10.742 10.814 10.772
    120 10.795 10.821 10.728 10.801 10.722 10.773
    三角 96 10.821 10.791 10.844 10.861 10.742 10.811
    108 10.994 11.069 10.711 10.670 10.781 10.845
    120 10.892 10.931 10.897 10.911 10.821 10.890
    圆形 96 10.873 10.810 10.822 10.789 10.867 10.832
    108 10.849 10.872 10.893 10.812 10.827 10.851
    120 10.974 10.912 10.812 10.832 10.844 10.874
    下载: 导出CSV

    表  4  Drones cube簇数与算法运行时长

    Table  4  Number of drones cube and algorithm running 09:42:00

    分布形式 簇数$L$ 算法运行时长$(\text{s})$ 平均时长$(\text{s})$
    第1次 第2次 第3次 第4次 第5次
    直线 3 10.644 10.685 10.673 10.731 10.508 10.648
    4 10.788 10.753 10.761 10.742 10.814 10.772
    5 10.821 10.876 10.824 10.897 10.933 10.870
    三角 3 10.878 10.787 10.709 10.801 10.822 10.799
    4 10.994 11.069 10.711 10.670 10.781 10.845
    5 10.892 10.977 11.021 10.709 10.898 10.899
    圆形 3 10.842 10.801 10.756 10.722 10.793 10.782
    4 10.849 10.872 10.893 10.812 10.827 10.851
    5 10.910 10.953 10.871 11.213 10.945 10.978
    下载: 导出CSV
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  • 收稿日期:  2018-03-14
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