Cooperative Search Optimization of an Unknown Dynamic Target Based on the Modified TPM
Aiming to address the problem of unknown dynamic target trajectory prediction and search path optimization in unmanned aerial vehicle (UAV) swarm path planning, this paper proposes a target search algorithm based on a modified target probability map (TPM). First, using the TPM, the proposed algorith...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | International Journal of Aerospace Engineering |
| Online Access: | http://dx.doi.org/10.1155/2022/8561245 |
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| _version_ | 1832568153255706624 |
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| author | Kaixin Cheng Di Wu Tao Hu Jinjin Wei Zhifu Tian |
| author_facet | Kaixin Cheng Di Wu Tao Hu Jinjin Wei Zhifu Tian |
| author_sort | Kaixin Cheng |
| collection | DOAJ |
| description | Aiming to address the problem of unknown dynamic target trajectory prediction and search path optimization in unmanned aerial vehicle (UAV) swarm path planning, this paper proposes a target search algorithm based on a modified target probability map (TPM). First, using the TPM, the proposed algorithm generates a high-probability distribution region of a target with directionality to fit the target trajectory and realizes the trajectory prediction of an unknown dynamic target. Then, the distributed ant colony (ACO) algorithm and the artificial potential field (APF) algorithm are combined to generate and optimize the UAV swarm search result and return path with the goal of maximizing task execution efficiency. Finally, the Monte Carlo simulation method is used to analyze the effectiveness of the proposed algorithm, and the results are evaluated from five aspects, including the number of targets captured. The simulation results show that under the condition of an unknown dynamic target trajectory, the average target captured rate and average unknown region search rate of the MTPM method were higher than that of the traditional TPM method, and the performance was improved by 14.6% and 10.7%, respectively. |
| format | Article |
| id | doaj-art-82c0fabad8fa45f1ba27d3e2cc5a3ea7 |
| institution | Kabale University |
| issn | 1687-5974 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Aerospace Engineering |
| spelling | doaj-art-82c0fabad8fa45f1ba27d3e2cc5a3ea72025-02-03T00:59:38ZengWileyInternational Journal of Aerospace Engineering1687-59742022-01-01202210.1155/2022/8561245Cooperative Search Optimization of an Unknown Dynamic Target Based on the Modified TPMKaixin Cheng0Di Wu1Tao Hu2Jinjin Wei3Zhifu Tian4College of Data Target EngineeringCollege of Data Target EngineeringCollege of Data Target EngineeringCollege of Information System EngineeringCollege of Data Target EngineeringAiming to address the problem of unknown dynamic target trajectory prediction and search path optimization in unmanned aerial vehicle (UAV) swarm path planning, this paper proposes a target search algorithm based on a modified target probability map (TPM). First, using the TPM, the proposed algorithm generates a high-probability distribution region of a target with directionality to fit the target trajectory and realizes the trajectory prediction of an unknown dynamic target. Then, the distributed ant colony (ACO) algorithm and the artificial potential field (APF) algorithm are combined to generate and optimize the UAV swarm search result and return path with the goal of maximizing task execution efficiency. Finally, the Monte Carlo simulation method is used to analyze the effectiveness of the proposed algorithm, and the results are evaluated from five aspects, including the number of targets captured. The simulation results show that under the condition of an unknown dynamic target trajectory, the average target captured rate and average unknown region search rate of the MTPM method were higher than that of the traditional TPM method, and the performance was improved by 14.6% and 10.7%, respectively.http://dx.doi.org/10.1155/2022/8561245 |
| spellingShingle | Kaixin Cheng Di Wu Tao Hu Jinjin Wei Zhifu Tian Cooperative Search Optimization of an Unknown Dynamic Target Based on the Modified TPM International Journal of Aerospace Engineering |
| title | Cooperative Search Optimization of an Unknown Dynamic Target Based on the Modified TPM |
| title_full | Cooperative Search Optimization of an Unknown Dynamic Target Based on the Modified TPM |
| title_fullStr | Cooperative Search Optimization of an Unknown Dynamic Target Based on the Modified TPM |
| title_full_unstemmed | Cooperative Search Optimization of an Unknown Dynamic Target Based on the Modified TPM |
| title_short | Cooperative Search Optimization of an Unknown Dynamic Target Based on the Modified TPM |
| title_sort | cooperative search optimization of an unknown dynamic target based on the modified tpm |
| url | http://dx.doi.org/10.1155/2022/8561245 |
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