摘要
随着各大国之间城市化进程的推进,城市环境中的无人机作战将成为未来必不可少的作战手段之一。针对城市作战环境复杂和作战装备受限的特点,归纳总结了无人机导航技术的研究现状和发展趋势,并给出相应的概念、模型以及被广泛应用的算法。首先,对单无人机定位技术进行了概括总结,包括全球卫星导航系统、惯性导航系统定位、视觉/激光雷达定位、无线传感网定位和融合定位等,上述定位方法能够在城市环境中表现出高精度和鲁棒性的特点;然后,为了解决单无人机在执行任务方面效率低、冗余低、易受干扰的特点,对无人机集群导航定位进行了介绍,主要包括全球导航卫星系统拒止下的导航定位、非视距及多径效应下的导航定位、基于无线传感网和视觉冗余的融合定位等,其中涉及导航恢复及导航增强等内容。最后,面对城市的复杂环境,提出了无人机导航定位技术的未来研究方向,分别为传感器的优化、无人机集群通信和多传感器融合,指出了未来的研究方向和面临的挑战。
With the advancement of urbanization of the great countries,UAV operations in urban environments will become one of the indispensable means of warfare in the future.In light of the characteristic of complex urban combat environment and limited combat equipment,this paper summarizes the research status and development trend of navigation and positioning technology for UAV,and the corresponding concepts,models and widely used algorithms are given.Firstly,this paper summarizes the single UAV positioning technology,including global satellite navigation system,inertial navigation system positioning,vision/lidar positioning,wireless sensor network positioning and fusion positioning.The above positioning methods can show high accuracy and robustness in urban environment.Then,in order to solve the problems of low efficiency,low redundancy and easy to be disturbed in the task execution of single UAV,this paper introduces the navigation and positioning of the UAV cluster,mainly including the global navigation satellite system(GNSS)navigation and positioning,navigation and positioning in the non line of sight(NLOS)and multi-path effect environment,and the fusion positioning based on wireless sensor network and visual redundancy,navigation recovery and navigation enhancement are involved.Finally,facing the complex urban environment,this paper proposes the future research directions of UAV navigation position technology,which are sensor optimization,UAV cluster communication and multi-sensor fusion.This paper discusses the operational scenarios of UAV navigation and positioning technology,comprehensively summarizes the current advanced technologies,and points out the future research directions and challenges.
作者
李楠
向文豪
LI Nan;XIANG Wenhao(A Military Representative Office of the Naval Equipment Department in Beijing,Beijing 100036,China;Systems Engineering Research Institute,CSSC,Beijing 100036,China)
出处
《无人系统技术》
2022年第4期75-87,共13页
Unmanned Systems Technology
关键词
协同导航
协同控制
任务规划
无人机
城市环境
无线传感网
多源融合
Cooperative Navigation
Collaborative Control
Mission Planning
UAV
Urban Environment
Wireless Sensor Network
Multi-source Fusion
