| 基于遗传算法的区域雷达网优化布站方法 |
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| 引用本文： | 杨仕明,柯炳清,薛正辉.基于遗传算法的区域雷达网优化布站方法[J].北京理工大学学报,2005,25(6):534-537. |
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| 作者姓名： | 杨仕明 柯炳清 薛正辉 |
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| 作者单位： | 北京理工大学,信息科学技术学院电子工程系,北京,100081;北京理工大学,信息科学技术学院电子工程系,北京,100081;北京理工大学,信息科学技术学院电子工程系,北京,100081 |
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| 摘 要： | 为提高区域雷达网探测能力和抗综合电子干扰、抗隐身技术与隐身飞机的威胁,抗低空、超低空突防及抗反辐射导弹(ARM)能力,提出了一种基于遗传算法的雷达网优化布站方法.建立区域雷达网优化布站的数学模型,给出遗传算法在该优化问题中的求解过程和步骤,为加快求解速度对遗传算法进行了改进,并进行了雷达组网仿真,将分析结果与应用模拟退火算法计算的结果进行了比较,结果表明该方法能够快速得出多种优化布站方案,并具有易操作性.
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| 关 键 词： | 遗传算法 雷达网 优化布站 探测概率 |
| 文章编号： | 1001-0645(2005)06-0534-04 |
| 收稿时间： | 7/5/2004 12:00:00 AM |
| 修稿时间： | 2004年7月5日 |
Approach to Regional Radar Netting Optimization Based on Genetic Algorithm |
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| YANG Shi-ming,KE Bing-qing and XUE Zheng-hui.Approach to Regional Radar Netting Optimization Based on Genetic Algorithm[J].Journal of Beijing Institute of Technology(Natural Science Edition),2005,25(6):534-537. |
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| Authors: | YANG Shi-ming KE Bing-qing and XUE Zheng-hui |
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| Institution: | Department of Electronic Engineering, School of Information Science and Technology, Beijing Institute of Technology, Beijing100081, China;Department of Electronic Engineering, School of Information Science and Technology, Beijing Institute of Technology, Beijing100081, China;Department of Electronic Engineering, School of Information Science and Technology, Beijing Institute of Technology, Beijing100081, China |
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| Abstract: | In order to improve the detective performance and the performance of anti synthesized electronic interference, anti stealth technique and stealth aircraft, anti low, ultra low altitude penetration and anti anti-radiation missiles (ARM), an optimal disposition method based on genetic algorithm is presented for radar netting. A mathematical model for radar optimal disposition is established according to the analysis of regional radar netting at the beginning. And then, the solving process of the genetic algorithm (GA) for this optimization problem is discussed, and the improved GA to expedite the solving velocity is presented. Finally, through analyzing an example and comparing the results with that of the simulated annealing algorithm, it comes to a conclusion that several netting schemes can be obtained much more quickly by this method with better operability. |
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| Keywords: | genetic algorithm radar network optimal disposition detective probability |
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