{"title":"Selected Issues and Constraints of Image Matching in Terrain-Aided Navigation: A Comparative Study","authors":"P. Turek, S. Grzywiński, W. Bużantowicz","doi":"10.5772/intechopen.95039","DOIUrl":null,"url":null,"abstract":"The sensitivity of global navigation satellite systems to disruptions precludes their use in conditions of armed conflict with an opponent possessing comparable technical capabilities. In military unmanned aerial vehicles (UAVs) the aim is to obtain navigational data to determine the location and correction of flight routes by means of other types of navigational systems. To correct the position of an UAV relative to a given trajectory, the systems that associate reference terrain maps with image information can be used. Over the last dozen or so years, new, effective algorithms for matching digital images have been developed. The results of their performance effectiveness are based on images that are fragments taken from source files, and therefore their qualitatively identical counterparts exist in the reference images. However, the differences between the reference image stored in the memory of navigation system and the image recorded by the sensor can be significant. In this paper modern methods of image registration and matching to UAV position refinement are compared, and adaptation of available methods to the operating conditions of the UAV navigation system is discussed.","PeriodicalId":127022,"journal":{"name":"Self-driving Vehicles and Enabling Technologies [Working Title]","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Self-driving Vehicles and Enabling Technologies [Working Title]","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5772/intechopen.95039","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The sensitivity of global navigation satellite systems to disruptions precludes their use in conditions of armed conflict with an opponent possessing comparable technical capabilities. In military unmanned aerial vehicles (UAVs) the aim is to obtain navigational data to determine the location and correction of flight routes by means of other types of navigational systems. To correct the position of an UAV relative to a given trajectory, the systems that associate reference terrain maps with image information can be used. Over the last dozen or so years, new, effective algorithms for matching digital images have been developed. The results of their performance effectiveness are based on images that are fragments taken from source files, and therefore their qualitatively identical counterparts exist in the reference images. However, the differences between the reference image stored in the memory of navigation system and the image recorded by the sensor can be significant. In this paper modern methods of image registration and matching to UAV position refinement are compared, and adaptation of available methods to the operating conditions of the UAV navigation system is discussed.