{"title":"IMU-Aided Geographic Pose Estimation Method for UAVs Using Satellite Imageries Matching","authors":"Yongfei Li","doi":"10.1109/LRA.2025.3536285","DOIUrl":null,"url":null,"abstract":"Estimating the geographic position of Unmanned Aerial Vehicles (UAVs) in the absence of Global Navigation Satellite Systems (GNSS) is crucial for enhancing flight safety. This paper presents a vision-based geolocalization method that matches images captured by onboard cameras with satellite imageries, utilizing attitude information from Inertial Measurement Units (IMUs). We introduce a two-point solution for the Perspective-n-Point (PnP) problem, specifically when the camera's pitch and roll angles are known. This approach is shown to be highly robust against image alignment errors and significantly improves position estimation accuracy. Experiments with both synthetic and real flight data confirm the effectiveness and reliability of the proposed method in practical applications.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 3","pages":"2902-2909"},"PeriodicalIF":4.6000,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Robotics and Automation Letters","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10857422/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ROBOTICS","Score":null,"Total":0}
引用次数: 0
Abstract
Estimating the geographic position of Unmanned Aerial Vehicles (UAVs) in the absence of Global Navigation Satellite Systems (GNSS) is crucial for enhancing flight safety. This paper presents a vision-based geolocalization method that matches images captured by onboard cameras with satellite imageries, utilizing attitude information from Inertial Measurement Units (IMUs). We introduce a two-point solution for the Perspective-n-Point (PnP) problem, specifically when the camera's pitch and roll angles are known. This approach is shown to be highly robust against image alignment errors and significantly improves position estimation accuracy. Experiments with both synthetic and real flight data confirm the effectiveness and reliability of the proposed method in practical applications.
期刊介绍:
The scope of this journal is to publish peer-reviewed articles that provide a timely and concise account of innovative research ideas and application results, reporting significant theoretical findings and application case studies in areas of robotics and automation.