Estimation of UAV position with use of thermal infrared images

Abstract

The 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.