An Airborne Multi-Sensor Task Allocation Method Based on Improved Particle Swarm Optimization Algorithm
The characteristics of airborne multi-sensor task allocation problem are analyzed, and an airborne multi-sensor task allocation model is established. In order to solve the problems of local convergence and slow convergence of the traditional Particle Swarm Optimization (PSO) algorithm, the structure...
| Format: | Article |
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| Language: | zho |
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EDP Sciences
2018-08-01
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| Series: | Xibei Gongye Daxue Xuebao |
| Subjects: | |
| Online Access: | https://www.jnwpu.org/articles/jnwpu/pdf/2018/04/jnwpu2018364p722.pdf |
| _version_ | 1797642733887684608 |
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| collection | DOAJ |
| description | The characteristics of airborne multi-sensor task allocation problem are analyzed, and an airborne multi-sensor task allocation model is established. In order to solve the problems of local convergence and slow convergence of the traditional Particle Swarm Optimization (PSO) algorithm, the structure and parameters of the existing Particle Swarm Optimization algorithm are adjusted, and the direction coefficient and far away factor are introduced to control the velocity and direction of the particle far away from the worst solution, so that the particle moves away from the worst solution while moving to the optimal solution. Based on the improved Particle Swarm Optimization algorithm, an airborne multi-sensor task allocation method is proposed using maximum detection probability as objective function, and the algorithm is simulated. The simulation results show that this algorithm can effectively allocate tasks and improve allocation effects. |
| first_indexed | 2024-03-11T14:04:34Z |
| format | Article |
| id | doaj.art-beba2ac03d8c458db7c436b461344bd7 |
| institution | Directory Open Access Journal |
| issn | 1000-2758 2609-7125 |
| language | zho |
| last_indexed | 2024-03-11T14:04:34Z |
| publishDate | 2018-08-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | Xibei Gongye Daxue Xuebao |
| spelling | doaj.art-beba2ac03d8c458db7c436b461344bd72023-11-02T03:09:29ZzhoEDP SciencesXibei Gongye Daxue Xuebao1000-27582609-71252018-08-0136472272710.1051/jnwpu/20183640722jnwpu2018364p722An Airborne Multi-Sensor Task Allocation Method Based on Improved Particle Swarm Optimization Algorithm01234School of Electronics and Information, Northwestern Polytechnical UniversitySchool of Electronics and Information, Northwestern Polytechnical UniversitySchool of Electronics and Information, Northwestern Polytechnical UniversityShenyang Aircraft Design & Research InstituteShenyang Aircraft Design & Research InstituteThe characteristics of airborne multi-sensor task allocation problem are analyzed, and an airborne multi-sensor task allocation model is established. In order to solve the problems of local convergence and slow convergence of the traditional Particle Swarm Optimization (PSO) algorithm, the structure and parameters of the existing Particle Swarm Optimization algorithm are adjusted, and the direction coefficient and far away factor are introduced to control the velocity and direction of the particle far away from the worst solution, so that the particle moves away from the worst solution while moving to the optimal solution. Based on the improved Particle Swarm Optimization algorithm, an airborne multi-sensor task allocation method is proposed using maximum detection probability as objective function, and the algorithm is simulated. The simulation results show that this algorithm can effectively allocate tasks and improve allocation effects.https://www.jnwpu.org/articles/jnwpu/pdf/2018/04/jnwpu2018364p722.pdftask allocationairborne multi-sensorimproved particle swarm optimization algorithmdetection probability |
| spellingShingle | An Airborne Multi-Sensor Task Allocation Method Based on Improved Particle Swarm Optimization Algorithm Xibei Gongye Daxue Xuebao task allocation airborne multi-sensor improved particle swarm optimization algorithm detection probability |
| title | An Airborne Multi-Sensor Task Allocation Method Based on Improved Particle Swarm Optimization Algorithm |
| title_full | An Airborne Multi-Sensor Task Allocation Method Based on Improved Particle Swarm Optimization Algorithm |
| title_fullStr | An Airborne Multi-Sensor Task Allocation Method Based on Improved Particle Swarm Optimization Algorithm |
| title_full_unstemmed | An Airborne Multi-Sensor Task Allocation Method Based on Improved Particle Swarm Optimization Algorithm |
| title_short | An Airborne Multi-Sensor Task Allocation Method Based on Improved Particle Swarm Optimization Algorithm |
| title_sort | airborne multi sensor task allocation method based on improved particle swarm optimization algorithm |
| topic | task allocation airborne multi-sensor improved particle swarm optimization algorithm detection probability |
| url | https://www.jnwpu.org/articles/jnwpu/pdf/2018/04/jnwpu2018364p722.pdf |