人工蜂群算法在空间定位的研究  

Research on artificial bee colony algorithm for spatial orientation

作　　者：霍桂利 HUO Guili(Shanxi University,Taiyuan 030006,China;Shanxi Architectural College,Jinzhong 030060,China)

机构地区：[1]山西大学 [2]山西建筑职业技术学院

出　　处：《现代电子技术》2019年第24期176-179,共4页Modern Electronics Technique

基　　金：山西省科技厅项目(2013041007-03)~~

摘　　要：在发声目标的定位监测中,空间的坐标位置和发声时刻均为未知,而确定这些因素也是空间定位监测的关键所在。文中提出改进型人工蜂群算法来实现空间定位功能,以便有效地确定空间发声点位置和发声时间。该算法利用快速群体搜索特性,解决算法后期搜索效率低下以及对初始值敏感的缺陷,减小了误差且提高了计算精度。实验结果表明,改进型人工蜂群算法在实际空间定位中既精确又稳定,并能有效提高定位的准确性,具有较高的应用价值。In location monitoring of acoustic target,the coordinate position and the phonation time in the space are unknown,but determining these factors is also the key to spatial location monitoring. An improved artificial bee colony algorithm is presented to realize the space positioning function,which can effectively determine the location and time of the spatial sounding point. The defects of sensitivity to initial value and low search efficiency existing in the later period of the algorithm are solved by the fast group search feature of the algorithm,which reduces the error and improves the calculation accuracy. The experimental results show that the improved artificial bee colony algorithm is accurate and stable in actual spatial positioning,can effectively improve the positioning accuracy,and has high application value.

关 键 词：空间发声目标 空间定位 人工蜂群算法 搜索效率 计算精度 定位监测 

分 类 号：TN911-34[电子电信—通信与信息系统] TP301.6[电子电信—信息与通信工程]