Optimization Algorithm for Multiple Phases Sectionalized Modulation Jamming Based on Particle Swarm Optimization
Due to the difficulty in deducing the corresponding relationship between results and parameter settings of multiple phases sectionalized modulation (MPSM) jamming, a problem occurs when obtaining the optimal local suppression jamming effect, which limits the practical application of MPSM jamming. Th...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-02-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/8/2/160 |
| _version_ | 1798042239037865984 |
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| author | Jiawei Jiang Yanhong Wu Hongyan Wang Yakun Lv Lei Qiu Daobin Yu |
| author_facet | Jiawei Jiang Yanhong Wu Hongyan Wang Yakun Lv Lei Qiu Daobin Yu |
| author_sort | Jiawei Jiang |
| collection | DOAJ |
| description | Due to the difficulty in deducing the corresponding relationship between results and parameter settings of multiple phases sectionalized modulation (MPSM) jamming, a problem occurs when obtaining the optimal local suppression jamming effect, which limits the practical application of MPSM jamming. The traditional method struggles to meet the requirements by setting fixed parameters or random parameters. Therefore, an optimization algorithm for MPSM jamming based on particle swarm optimization (PSO) is proposed in this study to produce the optimal local suppression jamming effect and determine its corresponding parameter settings. First, we analyzed the relationship between the degree of mismatch and local suppression jamming effect. Then, we set appropriate fitness function and fitness value. Finally, we used PSO to calculate parameter settings of a section situation and phase situation, which minimizes the fitness function and fitness value. The optimization algorithm avoids the tremendous computation of traversing all parameter settings, is stable, the results are repeatable, and the algorithm provides the optimal local suppression jamming effect under different conditions. The simulation experiments demonstrate the feasibility and effectiveness of the optimization algorithm. |
| first_indexed | 2024-04-11T22:32:45Z |
| format | Article |
| id | doaj.art-3bd1edfd0d824a198cb744ec1fedb063 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-04-11T22:32:45Z |
| publishDate | 2019-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-3bd1edfd0d824a198cb744ec1fedb0632022-12-22T03:59:18ZengMDPI AGElectronics2079-92922019-02-018216010.3390/electronics8020160electronics8020160Optimization Algorithm for Multiple Phases Sectionalized Modulation Jamming Based on Particle Swarm OptimizationJiawei Jiang0Yanhong Wu1Hongyan Wang2Yakun Lv3Lei Qiu4Daobin Yu5Department of Electronic and Optical Engineering, Space Engineering University, Beijing 101416, ChinaDepartment of Electronic and Optical Engineering, Space Engineering University, Beijing 101416, ChinaSchool of Space Information, Space Engineering University, Beijing 101416, ChinaDepartment of Electronic and Optical Engineering, Space Engineering University, Beijing 101416, ChinaDepartment of Electronic and Optical Engineering, Space Engineering University, Beijing 101416, ChinaBeijing Space Information Relay and Transmission Technology Center, Beijing 100000, ChinaDue to the difficulty in deducing the corresponding relationship between results and parameter settings of multiple phases sectionalized modulation (MPSM) jamming, a problem occurs when obtaining the optimal local suppression jamming effect, which limits the practical application of MPSM jamming. The traditional method struggles to meet the requirements by setting fixed parameters or random parameters. Therefore, an optimization algorithm for MPSM jamming based on particle swarm optimization (PSO) is proposed in this study to produce the optimal local suppression jamming effect and determine its corresponding parameter settings. First, we analyzed the relationship between the degree of mismatch and local suppression jamming effect. Then, we set appropriate fitness function and fitness value. Finally, we used PSO to calculate parameter settings of a section situation and phase situation, which minimizes the fitness function and fitness value. The optimization algorithm avoids the tremendous computation of traversing all parameter settings, is stable, the results are repeatable, and the algorithm provides the optimal local suppression jamming effect under different conditions. The simulation experiments demonstrate the feasibility and effectiveness of the optimization algorithm.https://www.mdpi.com/2079-9292/8/2/160optimization algorithmmultiple phases sectionalized modulation (MPSM) jammingparticle swarm optimization (PSO)local suppression jammingfitness function |
| spellingShingle | Jiawei Jiang Yanhong Wu Hongyan Wang Yakun Lv Lei Qiu Daobin Yu Optimization Algorithm for Multiple Phases Sectionalized Modulation Jamming Based on Particle Swarm Optimization Electronics optimization algorithm multiple phases sectionalized modulation (MPSM) jamming particle swarm optimization (PSO) local suppression jamming fitness function |
| title | Optimization Algorithm for Multiple Phases Sectionalized Modulation Jamming Based on Particle Swarm Optimization |
| title_full | Optimization Algorithm for Multiple Phases Sectionalized Modulation Jamming Based on Particle Swarm Optimization |
| title_fullStr | Optimization Algorithm for Multiple Phases Sectionalized Modulation Jamming Based on Particle Swarm Optimization |
| title_full_unstemmed | Optimization Algorithm for Multiple Phases Sectionalized Modulation Jamming Based on Particle Swarm Optimization |
| title_short | Optimization Algorithm for Multiple Phases Sectionalized Modulation Jamming Based on Particle Swarm Optimization |
| title_sort | optimization algorithm for multiple phases sectionalized modulation jamming based on particle swarm optimization |
| topic | optimization algorithm multiple phases sectionalized modulation (MPSM) jamming particle swarm optimization (PSO) local suppression jamming fitness function |
| url | https://www.mdpi.com/2079-9292/8/2/160 |
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