Distributed Extended Kalman Filtering Based Techniques for 3-D UAV Jamming Localization
Wireless networks are vulnerable to jamming attacks. Jamming in wireless communication becomes a major research problem due to ease in Unmanned Aerial Vehicle (UAV) launching and blocking of communication channels. Jamming is a subset of Denial of Service Attack (DoS) and an intentional interference...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-11-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/20/22/6405 |
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| author | Waleed Aldosari Muhammad Moinuddin Abdulah Jeza Aljohani Ubaid M. Al-Saggaf |
| author_facet | Waleed Aldosari Muhammad Moinuddin Abdulah Jeza Aljohani Ubaid M. Al-Saggaf |
| author_sort | Waleed Aldosari |
| collection | DOAJ |
| description | Wireless networks are vulnerable to jamming attacks. Jamming in wireless communication becomes a major research problem due to ease in Unmanned Aerial Vehicle (UAV) launching and blocking of communication channels. Jamming is a subset of Denial of Service Attack (DoS) and an intentional interference where the malicious node disrupts the wireless communication by increasing the noise at the receiver node through transmission interference signal towards the target channel. In this work, the considered jammer is a UAV hovering around the target area to block the communication channel between two transceivers. We proposed a three-dimensional (3-D) UAV jamming localization scheme to track and detect the jammer position at each time step by employing a single boundary node observer. For this purpose, we developed two distributed Extended Kalman Filter (EKF) based schemes: (1) the Distributed EKF (DEKF) scheme using the information of the received power from the jammer at a single nearby boundary node only and (2) Distance Ratio aided Distributed EKF (DEKF-DR) based scheme utilizing an edge node in addition to a single boundary node. Extensive simulations are conducted in order to evaluate the performance of the proposed distributed algorithms for a 3-D trajectory and compared with that of the conventional Centralized EKF (EKF-Centr) based method (which is also modified for the 3-D scenario). The results show the clear supremacy of the proposed distributed algorithms with much lesser complexity in contrast to the conventional EKF-Centr technique. |
| first_indexed | 2024-03-10T14:58:36Z |
| format | Article |
| id | doaj.art-2c631fe6af28450f8295f82652a4e717 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T14:58:36Z |
| publishDate | 2020-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-2c631fe6af28450f8295f82652a4e7172023-11-20T20:22:54ZengMDPI AGSensors1424-82202020-11-012022640510.3390/s20226405Distributed Extended Kalman Filtering Based Techniques for 3-D UAV Jamming LocalizationWaleed Aldosari0Muhammad Moinuddin1Abdulah Jeza Aljohani2Ubaid M. Al-Saggaf3Center of Excellence in Intelligent Engineering Systems, King Abdulaziz University, Jeddah 21589, Saudi ArabiaCenter of Excellence in Intelligent Engineering Systems, King Abdulaziz University, Jeddah 21589, Saudi ArabiaCenter of Excellence in Intelligent Engineering Systems, King Abdulaziz University, Jeddah 21589, Saudi ArabiaCenter of Excellence in Intelligent Engineering Systems, King Abdulaziz University, Jeddah 21589, Saudi ArabiaWireless networks are vulnerable to jamming attacks. Jamming in wireless communication becomes a major research problem due to ease in Unmanned Aerial Vehicle (UAV) launching and blocking of communication channels. Jamming is a subset of Denial of Service Attack (DoS) and an intentional interference where the malicious node disrupts the wireless communication by increasing the noise at the receiver node through transmission interference signal towards the target channel. In this work, the considered jammer is a UAV hovering around the target area to block the communication channel between two transceivers. We proposed a three-dimensional (3-D) UAV jamming localization scheme to track and detect the jammer position at each time step by employing a single boundary node observer. For this purpose, we developed two distributed Extended Kalman Filter (EKF) based schemes: (1) the Distributed EKF (DEKF) scheme using the information of the received power from the jammer at a single nearby boundary node only and (2) Distance Ratio aided Distributed EKF (DEKF-DR) based scheme utilizing an edge node in addition to a single boundary node. Extensive simulations are conducted in order to evaluate the performance of the proposed distributed algorithms for a 3-D trajectory and compared with that of the conventional Centralized EKF (EKF-Centr) based method (which is also modified for the 3-D scenario). The results show the clear supremacy of the proposed distributed algorithms with much lesser complexity in contrast to the conventional EKF-Centr technique.https://www.mdpi.com/1424-8220/20/22/6405jamming attacksUnmanned Aerial Vehicle (UAV)localizationExtended Kalman Filter (EKF) |
| spellingShingle | Waleed Aldosari Muhammad Moinuddin Abdulah Jeza Aljohani Ubaid M. Al-Saggaf Distributed Extended Kalman Filtering Based Techniques for 3-D UAV Jamming Localization Sensors jamming attacks Unmanned Aerial Vehicle (UAV) localization Extended Kalman Filter (EKF) |
| title | Distributed Extended Kalman Filtering Based Techniques for 3-D UAV Jamming Localization |
| title_full | Distributed Extended Kalman Filtering Based Techniques for 3-D UAV Jamming Localization |
| title_fullStr | Distributed Extended Kalman Filtering Based Techniques for 3-D UAV Jamming Localization |
| title_full_unstemmed | Distributed Extended Kalman Filtering Based Techniques for 3-D UAV Jamming Localization |
| title_short | Distributed Extended Kalman Filtering Based Techniques for 3-D UAV Jamming Localization |
| title_sort | distributed extended kalman filtering based techniques for 3 d uav jamming localization |
| topic | jamming attacks Unmanned Aerial Vehicle (UAV) localization Extended Kalman Filter (EKF) |
| url | https://www.mdpi.com/1424-8220/20/22/6405 |
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