| 基于无线紫外光隐秘通信的侦察无人机蜂群分簇算法 |
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| 引用本文： | 赵太飞,许杉,屈瑶,王晶,张杰.基于无线紫外光隐秘通信的侦察无人机蜂群分簇算法[J].电子与信息学报,2019,41(4):967-972. |
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| 作者姓名： | 赵太飞 许杉 屈瑶 王晶 张杰 |
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| 作者单位： | 西安理工大学自动化与信息工程学院 西安 710048;西南科技大学特殊环境机器人技术四川省重点实验室 绵阳 621010;西安理工大学自动化与信息工程学院 西安 710048;北京邮电大学电信工程学院 北京 100876 |
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| 基金项目： | 国家自然科学基金;西安市碑林区科技计划;陕西省教育厅服务地方专项;特殊环境机器人技术四川省重点实验室开放基金;西安市科学计划;陕西省重点产业链创新计划项目 |
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| 摘 要： | 针对复杂战场环境下无人机(UAV)蜂群的渗透侦察任务，考虑无人机间信息传输时能量消耗的不均匀性，影响侦察任务的高效实施，该文提出一种基于无线紫外光隐秘通信的侦察UAV蜂群分簇算法。该算法结合无线紫外光散射通信的优点，通过分簇拓扑管理机制对UAV蜂群进行能耗平衡。仿真结果表明，与现有算法相比，所提算法能够有效均衡网络能量消耗，提高网络的传输效率，并且选取合适的数据包长度及节点密度可延长UAV蜂群的生存周期。
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| 关 键 词： | 无人机蜂群 无线紫外光通信 分簇算法 能耗平衡 |
| 收稿时间： | 2018-05-22 |
Cluster-based Algorithm of Reconnaissance UAV Swarm Based on Wireless Ultraviolet Secret Communication |
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| Taifei ZHAO,Shan XU,Yao QU,Jing WANG,Jie ZHANG.Cluster-based Algorithm of Reconnaissance UAV Swarm Based on Wireless Ultraviolet Secret Communication[J].Journal of Electronics & Information Technology,2019,41(4):967-972. |
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| Authors: | Taifei ZHAO Shan XU Yao QU Jing WANG Jie ZHANG |
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| Affiliation: | 1.Faculty of Automation and Information Engineering, Xi’an University of Technology, Xi’an 710048, China2.Robot Technology Used for Special Environment Key Laboratory of Sichuan Province, Southwest University of Science and Technology, Mianyang 621010, China3.Faculty of Telecommunications Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China |
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| Abstract: | Focusing on the reconnaissance mission of Unmanned Aerial Vehicle (UAV) swarm under complex battlefield environment, the non-uniform energy consumption during the information transmission between UAVs affects the efficient implementation of the reconnaissance mission, thus a cluster-based algorithm of reconnaissance UAV swarm based on wireless ultraviolet secret communication is proposed. Combined the advantages of wireless ultraviolet scattering communication, this algorithm uses cluster topology management mechanism to balance the energy consumption of UAV swarm. Simulation results show that the algorithm can effectively balance the network energy consumption and improve the transmission efficiency of the network when compared with the existing algorithm, and the lifetime of swarm can be extended when selecting the appropriate packet length and node density. |
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