Filter Kalman for solving the problem of coordinates unmanned aerial vehicles
Unmanned aerial vehicles (UAVs) are increasingly used in military and scientific research. Some miniaturized UAVs rely entirely on the global positioning system (GPS) for navigation. GPS is vulnerable to accidental or deliberate interference that can cause it to fail. It is not unusual, even in a be...
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| Language: | English |
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Belarusian National Technical University
2019-07-01
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| Series: | Системный анализ и прикладная информатика |
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| Online Access: | https://sapi.bntu.by/jour/article/view/251 |
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| author | N. N. Arefyev |
| author_facet | N. N. Arefyev |
| author_sort | N. N. Arefyev |
| collection | DOAJ |
| description | Unmanned aerial vehicles (UAVs) are increasingly used in military and scientific research. Some miniaturized UAVs rely entirely on the global positioning system (GPS) for navigation. GPS is vulnerable to accidental or deliberate interference that can cause it to fail. It is not unusual, even in a benign environment, for a GPS outage to occur for periods of seconds to minutes. For UAVs relying solely on GPS for navigation such an event can be catastrophic. This article proposes an extended Kalman filter approach to estimate the location of a UAV when its GPS connection is lost, using inter-UAV distance measurements Increasing the accuracy of coordinate’s determination is one of the most crucial tasks of the modern UAV navigation. This task can be solved by using different variants of integration of navigation systems. One of the modern variants of integration is the combination of GPS/GLONASS-navigation with the extended Kalman filter, which estimates the accuracy recursively with the help of incomplete and noisy measurements. Currently different variations of extended Kalman filter exist and are under development, which include various number of variable states [1]. This article will show the utilization efficiency of extended Kalman filter in modern developments. |
| format | Article |
| id | doaj-art-2eff6fa1698f4c6e80ecc036468be0ce |
| institution | Kabale University |
| issn | 2309-4923 2414-0481 |
| language | English |
| publishDate | 2019-07-01 |
| publisher | Belarusian National Technical University |
| record_format | Article |
| series | Системный анализ и прикладная информатика |
| spelling | doaj-art-2eff6fa1698f4c6e80ecc036468be0ce2025-02-03T05:16:50ZengBelarusian National Technical UniversityСистемный анализ и прикладная информатика2309-49232414-04812019-07-0101263410.21122/2309-4923-2019-1-26-34190Filter Kalman for solving the problem of coordinates unmanned aerial vehiclesN. N. Arefyev0Belarusian National Technical UniversityUnmanned aerial vehicles (UAVs) are increasingly used in military and scientific research. Some miniaturized UAVs rely entirely on the global positioning system (GPS) for navigation. GPS is vulnerable to accidental or deliberate interference that can cause it to fail. It is not unusual, even in a benign environment, for a GPS outage to occur for periods of seconds to minutes. For UAVs relying solely on GPS for navigation such an event can be catastrophic. This article proposes an extended Kalman filter approach to estimate the location of a UAV when its GPS connection is lost, using inter-UAV distance measurements Increasing the accuracy of coordinate’s determination is one of the most crucial tasks of the modern UAV navigation. This task can be solved by using different variants of integration of navigation systems. One of the modern variants of integration is the combination of GPS/GLONASS-navigation with the extended Kalman filter, which estimates the accuracy recursively with the help of incomplete and noisy measurements. Currently different variations of extended Kalman filter exist and are under development, which include various number of variable states [1]. This article will show the utilization efficiency of extended Kalman filter in modern developments.https://sapi.bntu.by/jour/article/view/251kalman filtergpscoordinates uavmathematical modelingaerial vehiclevisual odometryprojective geometrycontrolnavigationintegration |
| spellingShingle | N. N. Arefyev Filter Kalman for solving the problem of coordinates unmanned aerial vehicles Системный анализ и прикладная информатика kalman filter gps coordinates uav mathematical modeling aerial vehicle visual odometry projective geometry control navigation integration |
| title | Filter Kalman for solving the problem of coordinates unmanned aerial vehicles |
| title_full | Filter Kalman for solving the problem of coordinates unmanned aerial vehicles |
| title_fullStr | Filter Kalman for solving the problem of coordinates unmanned aerial vehicles |
| title_full_unstemmed | Filter Kalman for solving the problem of coordinates unmanned aerial vehicles |
| title_short | Filter Kalman for solving the problem of coordinates unmanned aerial vehicles |
| title_sort | filter kalman for solving the problem of coordinates unmanned aerial vehicles |
| topic | kalman filter gps coordinates uav mathematical modeling aerial vehicle visual odometry projective geometry control navigation integration |
| url | https://sapi.bntu.by/jour/article/view/251 |
| work_keys_str_mv | AT nnarefyev filterkalmanforsolvingtheproblemofcoordinatesunmannedaerialvehicles |