基于低截获概率优化的雷达组网系统最优功率分配算法(英文)

时晨光 汪飞 周建江 陈军

时晨光, 汪飞, 周建江, 陈军. 基于低截获概率优化的雷达组网系统最优功率分配算法(英文)[J]. 雷达学报, 2014, 3(4): 465-473. doi: 10.3724/SP.J.1300.2014.13140
引用本文: 时晨光, 汪飞, 周建江, 陈军. 基于低截获概率优化的雷达组网系统最优功率分配算法(英文)[J]. 雷达学报, 2014, 3(4): 465-473. doi: 10.3724/SP.J.1300.2014.13140
Shi Chen-guang, Wang Fei, Zhou Jian-jiang, Chen Jun. Optimal Power Allocation Algorithm for Radar Network Systems Based on Low Probability of Intercept Optimization (in English)[J]. Journal of Radars, 2014, 3(4): 465-473. doi: 10.3724/SP.J.1300.2014.13140
Citation: Shi Chen-guang, Wang Fei, Zhou Jian-jiang, Chen Jun. Optimal Power Allocation Algorithm for Radar Network Systems Based on Low Probability of Intercept Optimization (in English)[J]. Journal of Radars, 2014, 3(4): 465-473. doi: 10.3724/SP.J.1300.2014.13140

基于低截获概率优化的雷达组网系统最优功率分配算法(英文)

doi: 10.3724/SP.J.1300.2014.13140
基金项目: 

Supported by the National Natural Science Foundation of China (61371170), Funding of Jiangsu Innovation Program for Graduate Education (CXLX13_154), the Fundamental Research Funds for the Central Universities, the Priority Academic Program Development of Jiangsu Higher Education Institutions (PADA), and Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, Nanjing University of Aeronautics and Astronautics.

Optimal Power Allocation Algorithm for Radar Network Systems Based on Low Probability of Intercept Optimization (in English)

Funds: 

Supported by the National Natural Science Foundation of China (61371170), Funding of Jiangsu Innovation Program for Graduate Education (CXLX13_154), the Fundamental Research Funds for the Central Universities, the Priority Academic Program Development of Jiangsu Higher Education Institutions (PADA), and Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, Nanjing University of Aeronautics and Astronautics.

  • 摘要: 针对现代电子战中对低截获概率(LPI)技术的需求,该文提出了一种基于LPI 性能优化的最优功率分配算法。该文首先推导了雷达组网系统的Schleher 截获因子。然后,以最小化系统的Schleher 截获因子为目标,在满足系统跟踪性能要求的前提下,通过优化组网雷达的功率配置,提升雷达组网系统的LPI 性能。并用基于非线性规划的遗传算法(NPGA)对此非凸、非线性约束优化问题进行了求解。仿真结果验证了所提算法的有效性。

     

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出版历程
  • 收稿日期:  2013-12-23
  • 修回日期:  2014-05-29
  • 网络出版日期:  2014-08-28

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