摘要
粒子群优化算法是一种新颖的进化算法,它基于群体迭代。群体中的粒子在解空间中追随适应度最优的粒子,调整速度与位置并搜索最优解。根据MUSIC算法的定向原理,建立适应度函数,利用粒子群算法对单矢量水听器方位估计算法进行优化。结果表明,优化后可以提高低信噪比时方位估计的精度,并实现对目标的三维定位,同时还可以避免因成阵所带来的使用限制。
Particle swarm optimization （PSO）algorithm is a new evolutionary optimization based on swarm iteration. Groups of particles follow fitness optimum particle in the solution space, adjusting position and velocity and search for the most optimal solution. According to MUSIC algorithm oriented principle, establish fitness function, and using PSO to optimize the method for estimating the target bearing by a single vector hydrophone. The results show that, after optimization, it can improve the low signal to noise ratio estimation and achieve the goal of positioning, at the same time, can also avoid the array brought about by the use of constraints.
出处
《舰船科学技术》
北大核心
2012年第11期112-116,共5页
Ship Science and Technology
关键词
粒子群算法
矢量水听器
MUSIC算法
方位估计
particle swarm optimization
vector hydrophone
MUSIC
estimation of target bearing
