Research on Combat Mission Configuration of Unmanned Aerial Vehicle Maritime Reconnaissance Based on Particle Swarm Optimization Algorithm
In recent years, in the classic battles and armed conflicts around the world, battlefield environment reconnaissance and the collection and processing of operational information play an increasingly critical role in the victory and defeat of the battlefield. Unmanned equipment, especially UAV equipm...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2024-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2024/9143774 |
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| _version_ | 1832553187232448512 |
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| author | Peng Dong Weibing Chen Kewen Wang Ke Zhou Wei Wang |
| author_facet | Peng Dong Weibing Chen Kewen Wang Ke Zhou Wei Wang |
| author_sort | Peng Dong |
| collection | DOAJ |
| description | In recent years, in the classic battles and armed conflicts around the world, battlefield environment reconnaissance and the collection and processing of operational information play an increasingly critical role in the victory and defeat of the battlefield. Unmanned equipment, especially UAV equipment, is used by more and more countries in the field of combat reconnaissance. Meanwhile, the types of UAV are gradually diversified with the change of operational requirements. UAVs adapted to different combat environments shine brightly on the battlefield. In terms of naval battle field, due to the limitations and deficiencies of reconnaissance methods such as surface radar, UAVs play a more prominent role in combat reconnaissance. There are more scenarios for UAVs to be used in combat reconnaissance in naval battle field and higher requirements for UAVs’ combat effectiveness. Therefore, this paper takes UAVs’ naval battle reconnaissance missions as the research object. By using PSO as the research method, this paper studies the combat reconnaissance task configuration of UAVs, hoping to contribute to the improvement of UAVs’ combat reconnaissance capability and combat effectiveness. |
| format | Article |
| id | doaj-art-4504d1f1e870464c9833628bfc3c43e0 |
| institution | Kabale University |
| issn | 1099-0526 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-4504d1f1e870464c9833628bfc3c43e02025-02-03T05:54:34ZengWileyComplexity1099-05262024-01-01202410.1155/2024/9143774Research on Combat Mission Configuration of Unmanned Aerial Vehicle Maritime Reconnaissance Based on Particle Swarm Optimization AlgorithmPeng Dong0Weibing Chen1Kewen Wang2Ke Zhou3Wei Wang4Department of Management Engineering and Equipment EconomicsDepartment of Management Engineering and Equipment EconomicsDepartment of Management Engineering and Equipment EconomicsDepartment of Management Engineering and Equipment EconomicsDepartment of Management Engineering and Equipment EconomicsIn recent years, in the classic battles and armed conflicts around the world, battlefield environment reconnaissance and the collection and processing of operational information play an increasingly critical role in the victory and defeat of the battlefield. Unmanned equipment, especially UAV equipment, is used by more and more countries in the field of combat reconnaissance. Meanwhile, the types of UAV are gradually diversified with the change of operational requirements. UAVs adapted to different combat environments shine brightly on the battlefield. In terms of naval battle field, due to the limitations and deficiencies of reconnaissance methods such as surface radar, UAVs play a more prominent role in combat reconnaissance. There are more scenarios for UAVs to be used in combat reconnaissance in naval battle field and higher requirements for UAVs’ combat effectiveness. Therefore, this paper takes UAVs’ naval battle reconnaissance missions as the research object. By using PSO as the research method, this paper studies the combat reconnaissance task configuration of UAVs, hoping to contribute to the improvement of UAVs’ combat reconnaissance capability and combat effectiveness.http://dx.doi.org/10.1155/2024/9143774 |
| spellingShingle | Peng Dong Weibing Chen Kewen Wang Ke Zhou Wei Wang Research on Combat Mission Configuration of Unmanned Aerial Vehicle Maritime Reconnaissance Based on Particle Swarm Optimization Algorithm Complexity |
| title | Research on Combat Mission Configuration of Unmanned Aerial Vehicle Maritime Reconnaissance Based on Particle Swarm Optimization Algorithm |
| title_full | Research on Combat Mission Configuration of Unmanned Aerial Vehicle Maritime Reconnaissance Based on Particle Swarm Optimization Algorithm |
| title_fullStr | Research on Combat Mission Configuration of Unmanned Aerial Vehicle Maritime Reconnaissance Based on Particle Swarm Optimization Algorithm |
| title_full_unstemmed | Research on Combat Mission Configuration of Unmanned Aerial Vehicle Maritime Reconnaissance Based on Particle Swarm Optimization Algorithm |
| title_short | Research on Combat Mission Configuration of Unmanned Aerial Vehicle Maritime Reconnaissance Based on Particle Swarm Optimization Algorithm |
| title_sort | research on combat mission configuration of unmanned aerial vehicle maritime reconnaissance based on particle swarm optimization algorithm |
| url | http://dx.doi.org/10.1155/2024/9143774 |
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