摘要
将模拟退火思想融入到遗传算法中,形成了另一种优化算法,即模拟退火遗传算法,将其应用于加权子空间(WSF)算法的目标方位(DOA)估计技术中,以求降低WSF算法的运算复杂度,提高DOA估计精度,同时又解决了基本遗传算法在DOA估计中易陷入局部最优、后期搜索迟钝等问题。计算机仿真结果表明:采用模拟退火遗传算法的DOA估计技术在低信噪比条件下比采用基本遗传算法、高斯-牛顿算法有更高的分辨概率,更小的均方误差。
The simulated annealing genetic algorithm is a new global optimization algorithm, and it is formed by integrating the simulated annealing into the genetic algorithm. Then the simulated annealing genetic algorithm is applied to the WSF algorithm of DOA estimation technique, in order to reduce the complexity of WSF algorithm and improve the DOA estima-tion precision. At the same time, the new algorithm can solve the low efficiency and easily falling into local optimum prob-lems of the basic genetic algorithm in DOA estimation. Computer simulation results show that, compared with the basic genetic algorithm, gauss-newton method, the DOA estimation technique based on simulated annealing genetic algorithm has higher resolution probability and smaller mean square error.
出处
《计算机工程与应用》
CSCD
2014年第12期266-270,共5页
Computer Engineering and Applications
关键词
遗传算法
模拟退火算法
波达方向(DOA)
genetic algorithm
simulated annealing genetic algorithm
Direction OfArrival（DOA）
