Research on Intelligent Cooperative Detection Technology for UAV Swarm
As unmanned aerial vehicle (UAV) technology rapidly progresses, UAVs have shown immense potential in reconnaissance and detection tasks. However, in complex and dynamic battlefield environments, the combat effectiveness of a standalone UAV is limited, making it challenging to meet the demands of modern warfare. Consequently, this research endeavors to investigate intelligent cooperative detection technology for UAV swarms to enhance the efficiency and precision of reconnaissance and detection operations. By incorporating swarm intelligence algorithms, this study achieves autonomous control, information sharing, and cooperative engagement among UAV swarms. We have developed an advanced communication system to guarantee real-time transmission of reconnaissance data among UAVs and employed intelligent algorithms to integrate and analyze this information for effective cooperative engagement. Experimental findings indicate that intelligent cooperative detection technology for UAV swarms can substantially improve the efficiency and accuracy of reconnaissance and detection, thereby expanding the reconnaissance scope and minimizing false alarms. This technology offers robust support for reconnaissance and detection missions in complex battlefield scenarios. Hence, intelligent cooperative detection technology for UAV swarms holds vast application potential and signifies a pivotal development trajectory in the realm of reconnaissance and detection in modern warfare.
Authors
- Ning Gao (ORCID: https://orcid.org/0000-0003-1605-4137)
- Haixia Bi (ORCID: https://orcid.org/0009-0003-2879-0550)
- Yixiao Xia (ORCID: https://orcid.org/0000-0003-0560-4869)
- Dongping Liao
- Dong Fang Yang (ORCID: https://orcid.org/0000-0002-0518-019X)
- Xiaochun Liu (ORCID: https://orcid.org/0000-0002-3536-511X)
- Ling‐Ling Chen (ORCID: https://orcid.org/0000-0002-3005-526X)
Institutions
- Guangxi University of Science and Technology (CN)
Publication Details
- Journal
- Journal of big data and computing.
- Published
- 2024-12-01
- DOI
- https://doi.org/10.62517/jbdc.202401423
- Primary Topic
- Advanced Algorithms and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00