Efficient Multi-Target Localization Using Dynamic UAV Clusters
This paper proposes a dynamic unmanned aerial vehicle (UAV) clustering model for multi-target localization in complex 3D environments, where mobility-aware cluster formation is integrated to enhance collaborative localization accuracy. We derive the Cramér–Rao lower bound (CRLB) for localization per...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-04-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/25/9/2857 |
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| author | Wei Gong Shuhan Lou Liyuan Deng Peng Yi Yiguang Hong |
| author_facet | Wei Gong Shuhan Lou Liyuan Deng Peng Yi Yiguang Hong |
| author_sort | Wei Gong |
| collection | DOAJ |
| description | This paper proposes a dynamic unmanned aerial vehicle (UAV) clustering model for multi-target localization in complex 3D environments, where mobility-aware cluster formation is integrated to enhance collaborative localization accuracy. We derive the Cramér–Rao lower bound (CRLB) for localization performance analysis under measurement and motion-induced uncertainties. To solve the NP-hard clustering problem, we develop the MDQPSO-ASA algorithm, which combines multi-swarm discrete quantum-inspired particle swarm optimization with adaptive simulated annealing, incorporating a repair mechanism to satisfy spatial and cardinality constraints. Simulation results demonstrate the algorithm’s superiority in localization accuracy, computational efficiency, and adaptability to varying UAV/target scales compared to baseline methods. The developed algorithm provides an effective solution for resource-constrained collaborative localization tasks in practical scenarios. |
| format | Article |
| id | doaj-art-750ef0ae24d9400f944ca1a7e58f63fa |
| institution | OA Journals |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-750ef0ae24d9400f944ca1a7e58f63fa2025-08-20T02:24:58ZengMDPI AGSensors1424-82202025-04-01259285710.3390/s25092857Efficient Multi-Target Localization Using Dynamic UAV ClustersWei Gong0Shuhan Lou1Liyuan Deng2Peng Yi3Yiguang Hong4Department of Control Science and Engineering, Tongji University, Shanghai 201804, ChinaDepartment of Control Science and Engineering, Tongji University, Shanghai 201804, ChinaDepartment of Control Science and Engineering, Tongji University, Shanghai 201804, ChinaDepartment of Control Science and Engineering, Tongji University, Shanghai 201804, ChinaDepartment of Control Science and Engineering, Tongji University, Shanghai 201804, ChinaThis paper proposes a dynamic unmanned aerial vehicle (UAV) clustering model for multi-target localization in complex 3D environments, where mobility-aware cluster formation is integrated to enhance collaborative localization accuracy. We derive the Cramér–Rao lower bound (CRLB) for localization performance analysis under measurement and motion-induced uncertainties. To solve the NP-hard clustering problem, we develop the MDQPSO-ASA algorithm, which combines multi-swarm discrete quantum-inspired particle swarm optimization with adaptive simulated annealing, incorporating a repair mechanism to satisfy spatial and cardinality constraints. Simulation results demonstrate the algorithm’s superiority in localization accuracy, computational efficiency, and adaptability to varying UAV/target scales compared to baseline methods. The developed algorithm provides an effective solution for resource-constrained collaborative localization tasks in practical scenarios.https://www.mdpi.com/1424-8220/25/9/2857multi-target localizationclustered UAV systemscombinatorial optimizationdynamic clusteringquantum-inspired optimization |
| spellingShingle | Wei Gong Shuhan Lou Liyuan Deng Peng Yi Yiguang Hong Efficient Multi-Target Localization Using Dynamic UAV Clusters Sensors multi-target localization clustered UAV systems combinatorial optimization dynamic clustering quantum-inspired optimization |
| title | Efficient Multi-Target Localization Using Dynamic UAV Clusters |
| title_full | Efficient Multi-Target Localization Using Dynamic UAV Clusters |
| title_fullStr | Efficient Multi-Target Localization Using Dynamic UAV Clusters |
| title_full_unstemmed | Efficient Multi-Target Localization Using Dynamic UAV Clusters |
| title_short | Efficient Multi-Target Localization Using Dynamic UAV Clusters |
| title_sort | efficient multi target localization using dynamic uav clusters |
| topic | multi-target localization clustered UAV systems combinatorial optimization dynamic clustering quantum-inspired optimization |
| url | https://www.mdpi.com/1424-8220/25/9/2857 |
| work_keys_str_mv | AT weigong efficientmultitargetlocalizationusingdynamicuavclusters AT shuhanlou efficientmultitargetlocalizationusingdynamicuavclusters AT liyuandeng efficientmultitargetlocalizationusingdynamicuavclusters AT pengyi efficientmultitargetlocalizationusingdynamicuavclusters AT yiguanghong efficientmultitargetlocalizationusingdynamicuavclusters |