Gravitational Search Algorithm Swarm-Based UAV Reconnaissance for Multiple Targets Detection in Unknown Environment
Target detection in an unknown environment is a crucial aspect of reconnaissance using a swarm of unmanned aerial vehicles (UAVs). An efficient target detection technique is required to minimize the number of iterations for searching and maximize the coverage area with respect to the number of itera...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10902366/ |
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| Summary: | Target detection in an unknown environment is a crucial aspect of reconnaissance using a swarm of unmanned aerial vehicles (UAVs). An efficient target detection technique is required to minimize the number of iterations for searching and maximize the coverage area with respect to the number of iterations and detected targets. This paper proposes a gravitational search algorithm (GSA) swarm-based UAV reconnaissance scheme to detect targets in an unknown environment. Additionally, different GSA-based searching methods are analyzed to identify the most efficient one with the minimum number of iterations and maximum coverage. Extensive simulations are performed, and the results of the proposed scheme are compared with existing search schemes. The results demonstrate that the proposed GSA swarm-based detection scheme requires fewer iterations and provides greater area coverage than existing UAV reconnaissance schemes for target detection in an unknown environment. |
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| ISSN: | 2169-3536 |