Simulation approval of information technology of optical channel aircraft navigation
DOI:
https://doi.org/10.18372/2310-5461.47.14935Keywords:
simulation approval, UAV, alternative navigation, optical channelAbstract
Experience in modern combat operations — including Eastern Ukraine — shows the effectiveness of reconnaissance unmanned aerial vehicles (UAVs) usage. An obvious way to navigate UAVs is to navigate with using GPS. Thereby, an effective countermeasure against UAVs is radio-frequency suppression of the GPS signal, which in turn raises the issue of autonomous UAV navigation, in particular with the usage of data from the UAV’s payload cameras. That is, the current direction of development of reconnaissance unmanned aerial vehicles (UAVs) is the development of new methods and algorithms for alternative navigation on the optical channel by terrain recognizing and determining coordinates in real time from the cameras of the target UAV only. The basis for solving this problem in terms of information technology are object search methods for known images in a digital image. In another way, considering the method of UAV navigation by the optical channel in combination with the task of developing the appropriate software and hardware complex (SHC), one of the stages of the mentioned process is the developed components testing. The publications analysis shows insufficient coverage of this aspect of the SHCs development.
The goal of this article is to describe the process of simulation testing of the UAV optical channel navigation method by developing the corresponding software.
Considering the complexity of the approbation process on UAV directly, as well as significant economic and/or time loss in case of failure, it makes sense to perform simulation on test data.
In this publication: the software for simulation approbation of navigation technology of the aircraft optical channel is developed, the simulation approbation by usage of it is performed, the correctness of work of the offered navigation technology is confirmed.
References
Lowe D. G. Object Recognition from Local Scale-Invariant Features. Proc. of the 7th IEEE International Conference on Computer Vision. September 1999. № 7. doi: 10.1109%2FICCV.1999.790410
Приставка П. О. Поліноміальні сплайни при обробці даних. Д.: Вид-во Дн-вського націон. ун-ту, 2004. 236 с.
Приставка П. О. Визначення особливостей зображень на основі комбінацій В-сплайнів другого порядку, близьких до інтерполяційних у середньому. Актуальні проблеми автоматизації та ін-формаційних технологій. 2015. Т. 19. С. 67-77. doi: 10.15421/431507
Приставка П.О., Сорокопуд В.І., Чирков А.В. Експериментальний зразок автоматизованої системи пошуку підозрілих об’єктів на відео з безпілотного повітряного судна. Системи озброєння і військова техніка. 2017. № 2(50). С. 26-32.
Prystavka P., Sorokopud V., Chyrkov A., Kovtun V. Automated Complex for Aerial Reconnaissance Tasks in Modern Armed Conflicts. CEUR Workshop Proceedings. 2019. Vol. 2588. P. 57-66. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083197274&partnerID=40
Піскунов О.Г., Юрчук І.А. Нанесення фотоматеріалів літального апарату на растрові карти відк-ритих картографічних сервісів. Наукоємні технології. 2018. № 4(36). С. 102-104. doi: 10.18372/2310-5461.36.12226
Buryi P., Pristavka P., Sushko V. Automatic Definition the Field of View of Camera of Unmanned Aerial Vehicle. Science-Based Technologies. 2016. №2(30). P. 151-155.
Піскунов О.Г., Юрчук І.А., Білянська Л.В. Визначення області бачення камери при аерофотоз-йомці. Наукоємні технології. 2018. № 3(35). С. 204-208. doi: 10.18372/2310-5461.35.11839