基于自适应遗传算法的空管雷达部署优化

Deployment Optimization for Air Traffic Radar based on AGA

针对当前民航空中交通监视雷达部署方面存在的问题,提出利用带精英选择策略的自适应遗传算法实现监视雷达部署优化。首先从区域管制区覆盖率、进近管制区双重覆盖率等关键指标出发,建立了雷达部署数学模型。为避免遗传算法局部收敛和随机发散,采用了可变的交叉概率和变异概率。最后,编程实现了该算法。仿真结果表明,自适应遗传算法能够在要求空域范围内快速收敛并得到全局最优部署方案,提升了雷达利用率和空域覆盖率。

In view of existing problems in the deployment of traffic surveillance radars in civil aviation,an adaptive genetic algorithm(AGA)with elite selection strategies is proposed to optimize the deployment of surveillance radars.Firstly,the radar deployment mathematical model is established based on the key indicators such as coverage of regional control zones and dual coverage of approach control zones.In order to avoid local convergence and random divergence of genetic algorithms,variable crossover and mutation probabilities are used.Finally,the algorithm is implemented by programming.Simulation results indicate that the adaptive genetic algorithm can quickly converge within the required airspace and obtain a global optimal deployment scheme,which improves the radar utilization and airspace coverage.