Distributed Cognitive Positioning System Based on Nearest Neighbor Association and Multi-Point Filter Initiation for UAVs Using DTMB and INS
Location is critical for the safe and effective completion of Unmanned Aerial Vehicle (UAV) missions. Since positioning errors tend to accumulate over time, uncorrected measurements from Inertial Navigation Systems (INSs) are unreliable. Aiming for UAV self-positioning under the challenges of a Glob...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-02-01
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| Series: | Drones |
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| Online Access: | https://www.mdpi.com/2504-446X/9/2/130 |
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| author | Li Zha Hai Zhang Na Wang Cancan Tao Kunfeng Lv Ruirui Zhang |
| author_facet | Li Zha Hai Zhang Na Wang Cancan Tao Kunfeng Lv Ruirui Zhang |
| author_sort | Li Zha |
| collection | DOAJ |
| description | Location is critical for the safe and effective completion of Unmanned Aerial Vehicle (UAV) missions. Since positioning errors tend to accumulate over time, uncorrected measurements from Inertial Navigation Systems (INSs) are unreliable. Aiming for UAV self-positioning under the challenges of a Global Navigation Satellite System (GNSS), this article integrates Digital Terrestrial Multimedia Broadcast (DTMB) signals and assisted INS components as external radiation sources for system design. The trigonometric geometry algorithm is proposed to estimate the pseudo-measurement, and the impact factors of the positioning error are analyzed. After filtering the pseudo-measurement by multi-point initiation, we designed a model for cross-regional positioning scenarios using the nearest-neighbor navigation association and scalar weighted distributed fusion. The simulation results demonstrate that the model can effectively track the target. Finally, the effectiveness of the positioning at a constant altitude is evaluated through different vehicle-mounted scenarios with a speed of 60 km/h. The experimental results show that the minimum positioning error can reach 18.95 m over a 525 m trajectory, thus meeting actual UAV requirements and having practical value. |
| format | Article |
| id | doaj-art-3ea8fc155a744e099d263ef8598aada6 |
| institution | DOAJ |
| issn | 2504-446X |
| language | English |
| publishDate | 2025-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj-art-3ea8fc155a744e099d263ef8598aada62025-08-20T03:12:18ZengMDPI AGDrones2504-446X2025-02-019213010.3390/drones9020130Distributed Cognitive Positioning System Based on Nearest Neighbor Association and Multi-Point Filter Initiation for UAVs Using DTMB and INSLi Zha0Hai Zhang1Na Wang2Cancan Tao3Kunfeng Lv4Ruirui Zhang5School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, ChinaSchool of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, ChinaBeijing Huahang Radio Measurement & Research Institute, Beijing 102401, ChinaSchool of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, ChinaBeijing Institute of Remote Sensing Equipment, Beijing 100854, ChinaBeijing Huahang Radio Measurement & Research Institute, Beijing 102401, ChinaLocation is critical for the safe and effective completion of Unmanned Aerial Vehicle (UAV) missions. Since positioning errors tend to accumulate over time, uncorrected measurements from Inertial Navigation Systems (INSs) are unreliable. Aiming for UAV self-positioning under the challenges of a Global Navigation Satellite System (GNSS), this article integrates Digital Terrestrial Multimedia Broadcast (DTMB) signals and assisted INS components as external radiation sources for system design. The trigonometric geometry algorithm is proposed to estimate the pseudo-measurement, and the impact factors of the positioning error are analyzed. After filtering the pseudo-measurement by multi-point initiation, we designed a model for cross-regional positioning scenarios using the nearest-neighbor navigation association and scalar weighted distributed fusion. The simulation results demonstrate that the model can effectively track the target. Finally, the effectiveness of the positioning at a constant altitude is evaluated through different vehicle-mounted scenarios with a speed of 60 km/h. The experimental results show that the minimum positioning error can reach 18.95 m over a 525 m trajectory, thus meeting actual UAV requirements and having practical value.https://www.mdpi.com/2504-446X/9/2/130trigonometric geometrytarget trackingnearest neighbor associationmulti-point initiationdistributed fusion |
| spellingShingle | Li Zha Hai Zhang Na Wang Cancan Tao Kunfeng Lv Ruirui Zhang Distributed Cognitive Positioning System Based on Nearest Neighbor Association and Multi-Point Filter Initiation for UAVs Using DTMB and INS Drones trigonometric geometry target tracking nearest neighbor association multi-point initiation distributed fusion |
| title | Distributed Cognitive Positioning System Based on Nearest Neighbor Association and Multi-Point Filter Initiation for UAVs Using DTMB and INS |
| title_full | Distributed Cognitive Positioning System Based on Nearest Neighbor Association and Multi-Point Filter Initiation for UAVs Using DTMB and INS |
| title_fullStr | Distributed Cognitive Positioning System Based on Nearest Neighbor Association and Multi-Point Filter Initiation for UAVs Using DTMB and INS |
| title_full_unstemmed | Distributed Cognitive Positioning System Based on Nearest Neighbor Association and Multi-Point Filter Initiation for UAVs Using DTMB and INS |
| title_short | Distributed Cognitive Positioning System Based on Nearest Neighbor Association and Multi-Point Filter Initiation for UAVs Using DTMB and INS |
| title_sort | distributed cognitive positioning system based on nearest neighbor association and multi point filter initiation for uavs using dtmb and ins |
| topic | trigonometric geometry target tracking nearest neighbor association multi-point initiation distributed fusion |
| url | https://www.mdpi.com/2504-446X/9/2/130 |
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