Radar Tracking and Identification of Biobimetic UAV Cluster Targets
The rise of biomimetic unmanned aerial vehicle (UAV) cluster has brought new challenges for radar target tracking and identification. Different cluster flight modes will have different impacts on radar data processing and cluster target identification. For analyzing the influence mechanism of the cl...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Aero Weaponry
2023-06-01
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| Series: | Hangkong bingqi |
| Subjects: | |
| Online Access: | https://www.aeroweaponry.avic.com/fileup/1673-5048/PDF/2022-00230.pdf |
| _version_ | 1827825430592225280 |
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| author | Gao Wei, Rao Bin, Zhou Yongkun |
| author_facet | Gao Wei, Rao Bin, Zhou Yongkun |
| author_sort | Gao Wei, Rao Bin, Zhou Yongkun |
| collection | DOAJ |
| description | The rise of biomimetic unmanned aerial vehicle (UAV) cluster has brought new challenges for radar target tracking and identification. Different cluster flight modes will have different impacts on radar data processing and cluster target identification. For analyzing the influence mechanism of the cluster on radar tracking and identification, this paper models the flight process of UAV cluster based on three kinds of species: geese, wolves and bees, which respectively simulated the large-scale transport, close-in rounding attack and robust information communication of UAV cluster. Secondly, it discusses the influence mechanism of different cluster modes on several algorithms of tracking: track initiation, data association and tracking filter. Finally, combined with the characteristics of three biological movements, it designs the identification methods of cluster event pattern based on clustering in detail, and gives the judgment rules. The simulation results show that there is the suitable combination of radar data processing algorithms for different clustering modes. The optimized tracking algorithm combination based on different clustering modes can effectively improve the tracking accuracy of the radar cluster target, and can reduce the time cost. Moreover, the method proposed in this paper can realize the identification of different cluster patterns to the judgment of target intention and provide the subsequent processing. |
| first_indexed | 2024-03-12T02:49:59Z |
| format | Article |
| id | doaj.art-24bd29f541564e0d8f4267dfd7079214 |
| institution | Directory Open Access Journal |
| issn | 1673-5048 |
| language | zho |
| last_indexed | 2024-03-12T02:49:59Z |
| publishDate | 2023-06-01 |
| publisher | Editorial Office of Aero Weaponry |
| record_format | Article |
| series | Hangkong bingqi |
| spelling | doaj.art-24bd29f541564e0d8f4267dfd70792142023-09-04T03:14:28ZzhoEditorial Office of Aero WeaponryHangkong bingqi1673-50482023-06-0130310311110.12132/ISSN.1673-5048.2022.0230Radar Tracking and Identification of Biobimetic UAV Cluster TargetsGao Wei, Rao Bin, Zhou Yongkun0School of Electronics and Communication Engineering, Sun Yat-sen University, Shenzhen 518107, ChinaThe rise of biomimetic unmanned aerial vehicle (UAV) cluster has brought new challenges for radar target tracking and identification. Different cluster flight modes will have different impacts on radar data processing and cluster target identification. For analyzing the influence mechanism of the cluster on radar tracking and identification, this paper models the flight process of UAV cluster based on three kinds of species: geese, wolves and bees, which respectively simulated the large-scale transport, close-in rounding attack and robust information communication of UAV cluster. Secondly, it discusses the influence mechanism of different cluster modes on several algorithms of tracking: track initiation, data association and tracking filter. Finally, combined with the characteristics of three biological movements, it designs the identification methods of cluster event pattern based on clustering in detail, and gives the judgment rules. The simulation results show that there is the suitable combination of radar data processing algorithms for different clustering modes. The optimized tracking algorithm combination based on different clustering modes can effectively improve the tracking accuracy of the radar cluster target, and can reduce the time cost. Moreover, the method proposed in this paper can realize the identification of different cluster patterns to the judgment of target intention and provide the subsequent processing.https://www.aeroweaponry.avic.com/fileup/1673-5048/PDF/2022-00230.pdf|biomimetic group|uav cluster|geese|wolves|bees|radar target tracking |
| spellingShingle | Gao Wei, Rao Bin, Zhou Yongkun Radar Tracking and Identification of Biobimetic UAV Cluster Targets Hangkong bingqi |biomimetic group|uav cluster|geese|wolves|bees|radar target tracking |
| title | Radar Tracking and Identification of Biobimetic UAV Cluster Targets |
| title_full | Radar Tracking and Identification of Biobimetic UAV Cluster Targets |
| title_fullStr | Radar Tracking and Identification of Biobimetic UAV Cluster Targets |
| title_full_unstemmed | Radar Tracking and Identification of Biobimetic UAV Cluster Targets |
| title_short | Radar Tracking and Identification of Biobimetic UAV Cluster Targets |
| title_sort | radar tracking and identification of biobimetic uav cluster targets |
| topic | |biomimetic group|uav cluster|geese|wolves|bees|radar target tracking |
| url | https://www.aeroweaponry.avic.com/fileup/1673-5048/PDF/2022-00230.pdf |
| work_keys_str_mv | AT gaoweiraobinzhouyongkun radartrackingandidentificationofbiobimeticuavclustertargets |