Yachun Wan, Chaojun Sun, H. Fu, Biao Zhang, Wanhua Fan
{"title":"基于遗传算法的雷达搜索资源自适应优化方法","authors":"Yachun Wan, Chaojun Sun, H. Fu, Biao Zhang, Wanhua Fan","doi":"10.1109/CISS57580.2022.9971335","DOIUrl":null,"url":null,"abstract":"In the case of limited radar resources and multiple high-speed targets penetrating at the same time, in order to make the radar can focus more resources to search for high threat targets, an adaptive optimization method of radar search resources based on genetic algorithm is proposed. Considering the influence of crossover probability and mutation probability on the algorithm, the solving steps of genetic algorithm such as coding method and genetic operation are designed. The optimal allocation of search resources among the targets is analyzed under the fitness function of expected discovery distance, and the optimal allocation of search resources among targets is analyzed under the fitness functions of expected discovery distance and expected discovery time. The simulation results show that the adaptive optimization method of radar search resources based on genetic algorithm is superior to the traditional Equal Adjustment Strategy (EAS) method under the condition of limited search resources.","PeriodicalId":331510,"journal":{"name":"2022 3rd China International SAR Symposium (CISS)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Adaptive Optimization Method of Radar Search Resources Based on Genetic Algorithm\",\"authors\":\"Yachun Wan, Chaojun Sun, H. Fu, Biao Zhang, Wanhua Fan\",\"doi\":\"10.1109/CISS57580.2022.9971335\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the case of limited radar resources and multiple high-speed targets penetrating at the same time, in order to make the radar can focus more resources to search for high threat targets, an adaptive optimization method of radar search resources based on genetic algorithm is proposed. Considering the influence of crossover probability and mutation probability on the algorithm, the solving steps of genetic algorithm such as coding method and genetic operation are designed. The optimal allocation of search resources among the targets is analyzed under the fitness function of expected discovery distance, and the optimal allocation of search resources among targets is analyzed under the fitness functions of expected discovery distance and expected discovery time. The simulation results show that the adaptive optimization method of radar search resources based on genetic algorithm is superior to the traditional Equal Adjustment Strategy (EAS) method under the condition of limited search resources.\",\"PeriodicalId\":331510,\"journal\":{\"name\":\"2022 3rd China International SAR Symposium (CISS)\",\"volume\":\"109 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 3rd China International SAR Symposium (CISS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CISS57580.2022.9971335\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 3rd China International SAR Symposium (CISS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISS57580.2022.9971335","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaptive Optimization Method of Radar Search Resources Based on Genetic Algorithm
In the case of limited radar resources and multiple high-speed targets penetrating at the same time, in order to make the radar can focus more resources to search for high threat targets, an adaptive optimization method of radar search resources based on genetic algorithm is proposed. Considering the influence of crossover probability and mutation probability on the algorithm, the solving steps of genetic algorithm such as coding method and genetic operation are designed. The optimal allocation of search resources among the targets is analyzed under the fitness function of expected discovery distance, and the optimal allocation of search resources among targets is analyzed under the fitness functions of expected discovery distance and expected discovery time. The simulation results show that the adaptive optimization method of radar search resources based on genetic algorithm is superior to the traditional Equal Adjustment Strategy (EAS) method under the condition of limited search resources.