自动化学报2025，Vol.51Issue(2)：287-311,25.DOI:10.16383/j.aas.c230778
景象匹配无人机视觉定位
Drone-based Scene Matching Visual Geo-localization
摘要
Abstract
Drones play an important role in vicinagearth security,post-disaster rescue,geological survey,agricultur-al plant protection,and other fields due to their high flexibility,and they receive increasing attention.As a key technology in drones,positioning and navigation are crucial for whether the drone can successfully perform tasks.Currently,the main positioning and navigation algorithms include the global navigation satellite system,inertial po-sitioning,and scene matching positioning and navigation.Among them,the scene matching positioning and naviga-tion method uses computer vision technology to encode the digital features of aerial images collected during the flight of drones.Then,by constructing a similarity measurement and retrieval model,it measures the similarity between the aerial image features and the pre-obtained remote sensing map library features to complete the scene matching.Finally,based on the matching results of drone aerial images and remote sensing satellite maps,it ob-tains the corresponding geographic position information and updates it as the positioning result of the drone.The scene matching positioning and navigation method eliminates the dependence of the positioning system on position-ing signals and realizes the autonomy of drone flight positioning.This paper follows the feature extraction methods in the scene matching algorithm and outlines the development process of scene matching based on template match-ing,manual feature-based,and metric learning-based approaches while summarizing the key problems in the posi-tioning and navigation methods of scene matching.Finally,this paper summarizes the urgent problems that need to be solved in drone scene matching localization methods based on the current development status of scene matching algorithms.关键词
临地安防/无人机/视觉定位/景象匹配/度量学习/多视角变化Key words
Vicinagearth security/drone/visual geo-localization/scene matching/metric learning/multi-view changes引用本文复制引用
袁媛,孙柏,刘赶超..景象匹配无人机视觉定位[J].自动化学报,2025,51(2):287-311,25.基金项目
国家自然科学基金(62273282,62201471)资助Supported by National Natural Science Foundation of China(62273282,62201471) （62273282,62201471）
