基于遗传算法的光电组网优化布站  

Approach to optimal disposition of EO netting based on genetic algorithm

作　　者：李向军[1] 

机构地区：[1]海军驻西安二十所军事代表室,陕西西安710068

出　　处：《应用光学》2016年第1期6-11,共6页Journal of Applied Optics

摘　　要：单部光电的探测能力有限,采用多部光电组网的方法能够提高光电探测的空域和时域覆盖能力。为提高区域防空光电组网的探测概率和对抗来袭目标的能力,提出一种基于遗传算法的光电组网优化布站方法。建立区域覆盖能力最大化的优化布站数学模型,利用遗传算法求解光电组网布站的最优方案,给出组网各光电的位置坐标。通过Matlab编制相关遗传算法仿真程序,经计算,进化60代后,得出最大区域覆盖能力为fmax=0.681的优化布站方案,并绘制针对4类目标的光电探测覆盖区域图,验证了方法的理论可行性。The power of single EO detector is limited, so EO netting is used to improve the o- vercast power in airspace and time domain. In order to improve the detecting probability and ability of EO netting to against the attacting target, an optimal dispostion method based on genetic algorithm（GA） was presented for EO netting. A mathematical model was established for optimal disposition to getting the maximal overcast region, then the optimal disposition scheme and the coordinates of EO detectors in the netting were afforded by using the genetic algo- rithm. At last, the optimal disposition scheme and the figures of the detecting overcast region for 4 kinds of targets were given by Matlab simulation, and the maximal overcast region fmax was 0. 681 after 60 times of iteration. The feasibility of the proposed method was proved.

关 键 词：光电组网 遗传算法 探测能力 优化布站 

分 类 号：TN202[电子电信—物理电子学]