基于改进自适应遗传算法的MIMO雷达阵列优化  

Array Optimization for MIMO Radar Based on Improved Adaptive Genetic Algorithm

作　　者：梁浩[1] 李小波[1] 徐旭宇[1] 

机构地区：[1]电子工程学院,合肥230037

出　　处：《微波学报》2013年第4期12-19,共8页Journal of Microwaves

摘　　要：针对传统遗传算法在全局搜索和收敛方面的不足,提出一种改进自适应遗传算法。算法改进了自适应规则,采用随迭代次数和种群适应度自适应变化的交叉、变异操作,同时采用新的选择算子和改进后的最优精英保留策略,摒弃了传统轮盘赌博选择法,增加了收敛于全局最优解的概率,加快了收敛速度。通过测试函数优化求解试验证明,改进算法能够有效提高搜索过程种群的多样性,具有更快的收敛性和更好的全局最优性。在此基础上,将改进的自适应遗传算法应用到MIMO雷达阵列优化设计,通过稀疏栅格编码,采用同时考虑副瓣电平与波束宽度的双适应函数,使优化得到的MIMO雷达方向图具有更好的综合性能,更利于实际工程应用。最后仿真实验结果进一步验证了本文改进算法的有效性。An improved adaptive genetic algorithm is proposed to solve the problem in which traditional genetic algo- rithm has deficiencies in global search and convergence speed. It modifies the adaptive technology by adopting the crossover and mutation operator adaptive adjusting with the number of iterations and fitness of populations. And the traditional selection operator based on roulette is replaced by new selection operator and improved elite reservation strategy to increase the proba- bility of the global best answer and speed up the convergence rate. Through the experiments of optimization for common func- tions, the improved algorithm can enhance the number of elite and show the better global optimal ability and faster conver- gence ability. Based on this, the improved algorithm is applied in the array optimization of MIMO radar. Through the grid coding and using the bi-fitness function considering both sidelobe level and mainlobe width, the better synthetical perform- ance of the array pattern for MIMO radar can be obtained, which will be more available in practice. Simulation results verify that the proposed algorithm is effective.

关 键 词：改进自适应遗传算法 MIMO雷达 阵列优化 双适应度函数 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]