摘要
针对子空间拟合算法对独立信源和相干信源求解过程中,多维搜索运算量大的问题,通过采用实数编码的量子位表示染色体和用量子旋转门更新量子位的方法,提出一种实数编码的量子遗传方法(RC-QGA)来实现加权信号子空间拟合(WSSF)测向,从而有效地降低传统算法的计算量.还研究了WSSF算法的一维解相干性能和二维波达方向(DOA)估计性能.实验仿真表明,RC-QGA方法在进化代数为10时就可以达到收敛,有效提高了传统遗传算法的收敛性能,并且具有计算量小和估计性能优良的特点.
The process of solving subspace fitting algorithm is a multi-dimensional search process requesting large amount of computation. In this paper, we propose a new method called real-coded quantum genetic algorithm （ RC- QGA） which is based on quantum rotary gate and genetic algorithm to realize weighted signal subspace fitting （WSSF） algorithm. This method effectively reduces the computational complexity. This paper researches on the performance of coherent sources and direction of arrival （DOA） estimation for two dimensional signals. Simulation results show that the RC-QGA algorithm can estimate coherent sources as well as two dimensional signals and has much better estimation performance than that of genetic algorithm （GA）.
出处
《应用科技》
CAS
2010年第3期49-52,共4页
Applied Science and Technology
