MUSIC算法结合小生境遗传算法的电磁矢量传感器波达方向估计  

MUSIC Method Combined with a Genetic Algorithm for 2-D Direction Finding Estimation wigh Electromagnetic Vector Sensor Arrays

作　　者：季飞[1] 郑乐[1] 文斐[1] 

机构地区：[1]华南理工大学电子与信息学院,广州510640

出　　处：《科学技术与工程》2009年第14期4012-4016,4023,共6页Science Technology and Engineering

基　　金：国家自然科学基金(60672065)资助

摘　　要：当最大似然估计法和MUSIC算法求解矢量传感器阵列问题时,存在多维谱峰搜索的困难。采用一种小生境遗传算法用于矢量传感器阵列的MUSIC算法的多谱峰搜索。通过实验仿真,验证了小生境算法的有效性。仿真结果表明,基于遗传算法的MUSIC算法得到的角度估计均方根偏差性能比ESPRIT算法要差,而在均方根标准方差方面,基于遗传算法的MUSIC算法则比ESPRIT算法要好。The maximum likelihood （ML） approach and MUSIC-based algorithm for 2-D direction finding estimation with electromagnetic vector sensor arrays require a multi-dimensional spectral peak search. One niche genetic algorithm is presented for MUSIC 2-D direction finding estimation method wigh electromagnetic vector sensor arrays. Numerical simulations testified the validity of the niche genetic algorithm. Simulation results show that the RMS bias performance of angle estimates from MUSIC combined with niche genetic algorithm is worse than that from ESPRIT algorithm. But the RMS Standard deviation performance of angle estimates obtained from MUSIC combined with niche genetic algorithm is better than that from ESPRIT algorithm.

关 键 词：DOA(E-D Direction ofArriral)估计 遗传算法 电磁矢量传感器 多信号分类算法(Multiple Signal Classification MUSIC)算法 

分 类 号：TN911.7[电子电信—通信与信息系统]