摘要
对空间多个窄带信号源的高分辨波达方向估计是移动通信、雷达、声纳、电子监控和地震研究等信号处理中的重要问题之一。而现在的一些获取波达方向估计最大似然解的算法存在收敛速度慢或者局部极值问题,为了克服这些问题,本文以粒子群算法为基础,在粒子群算法的速度更新公式基础上考虑了粒子平均信息的影响,并对惯性因子进行改进,考虑了当前粒子与当前最优粒子之间的距离,并用其来寻求波达方向最大似然估计的全局最优解。仿真结果表明:与改进前的粒子群算法相比,基于改进粒子群优化算法的波达方向估计在提高搜索全局最优速度和估计精度上都有优势。
The problem of obtaining the high resolution direction of arrival (DOA) estimation of narrow-band sources lying in the far field of array is one of the central problems in mobile communication, radar, electronic monitoring and seismology. To overcome the slow convergence speed or the local optimal problem existing in some maximum likelihood DOA estimation algorithms and improve the estimation accuracy, a global optimal solution of nonlinear maximum likelihood DOA estimation is obtained by an improved PSO algo- rithm in this paper. This algorithm is based on PSO algorithm and improves the formula of velocity renewal with the influence of average information and inertia weight with the distance between current particle and best particle. Simulation results show that DOA estimation based on this improved PSO algorithm performs better than before, and its feasibility is proved by computer simulation.
出处
《信号处理》
CSCD
北大核心
2009年第8期1304-1308,共5页
Journal of Signal Processing
基金
国家自然科学基金(60672034)
关键词
波达方向估计
最大似然估计
粒子群优化算法
全局优化
direction of arrival(DOA) estimation
maximum likelihood estimation
Particle Swarm Optimization
global optimi-zation