基于量子遗传算法的雷达组网布站分析

针对弹道目标雷达组网测试,测量设备布站设计是一个典型的复杂优化问题。基于量子遗传算法搜索机理和待求解优化问题特性,以弹道测量精度为目标函数,设计了优化算法计算流程。对一种多雷达设备组网布站测量进行了仿真评估,重点关注了量子遗传算法2种旋转角策略对搜索全局最优解的影响。结果表明:区别于旋转角变小的更新策略,旋转角变大的更新策略虽然收敛速度下降,但获得全局最优解的概率增大。研究结果为量子遗传算法在弹道组网测试领域的应用提供了参考。

Analysis of Radar Netting Disposition Based on Quantum Genetic Algorithm

Aiming at the radar network test for ballistic target,the measurement equipment disposition design is a typical complex optimization problem. Based on the quantum genetic algorithm search mechanism and the characteristics of the optimization problem,the optimization algorithm calculation flow was designed by taking the ballistic measurement accuracy as objective function. The simulation was carried out to estimate the multi-radar equipment network measurement,and the influence of two rotation-angle strategies of quantum genetic algorithm on the search for global optimization solution was studied. Compared with the strategy of diminishing rotation angle,the strategy of increasing rotation-angle improves the probability of obtaining the global optimal solution,although the convergence speed decreases.The result offers reference for the application of quantum genetic algorithm in the field of network test.