@InProceedings{SilvaShigVijaCamp:2016:EsUAPo,
               author = "Silva, Wanessa da and Shiguemori, Elcio Hideiti and Vijaykumar, 
                         Nandamudi Lankalapalli and Campos Velho, Haroldo Fraga de",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         de Estudos Avan{\c{c}}ados (IEAv)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)}",
                title = "Estimation of UAV position with use of thermal infrared images",
                 year = "2016",
                pages = "828--833",
         organization = "International Conference on Sensing Technology, 9.",
            publisher = "IEEE",
             abstract = "he use of Unmanned Aerial Vehicles has increased and become 
                         indispensable for many applications where human intervention is 
                         exhausting, dangerous or expensive. With this increase in UAV 
                         employment, autonomous navigation has been the subject of several 
                         studies. For this purpose, several systems have been used, among 
                         them, image processing, that is an alternative to the Global 
                         Positioning System. The employment of images in an autonomous 
                         navigation system has challenges, among them, the night flight. In 
                         this context, this article presents a study to estimate the UAV's 
                         geographical position with use of infrared images. From this 
                         image, a search is made in a georeferenced satellite image in the 
                         visible band. To automatically register between aerial and 
                         satellite images, edge information extracted by Artificial Neural 
                         Networks are used. The artificial neural network is automatically 
                         configured with use of Multiple Particle Collision Algorithm. 
                         Furthermore, the estimation of the UAV's position is obtained by 
                         calculating the correlation index. The results are promissing to 
                         be employed in night autonomous navigation.",
  conference-location = "New Zealand",
      conference-year = "8-11 dec. 2015",
                  doi = "10.1109/ICSensT.2015.7438511",
                  url = "http://dx.doi.org/10.1109/ICSensT.2015.7438511",
                 isbn = "978-147996314-0",
                 issn = "21568065",
             language = "en",
        urlaccessdate = "28 abr. 2024"
}