学术论文

      基于GSO与加权质心的DV-Hop定位算法

      DV-Hop Localization Algorithm Based on GSO and Weighted Centroid

      摘要:
      由于经典DV-Hop定位算法中定位精度较低,提出一种改进算法.首先,未知节点计算到各信标节点的距离时,采用不同平均每跳距离.其次,采用GSO(galactic swarm optimization)思想把网络中的信标节点分为不同种群,使用粒子群优化算法估计每个种群中未知节点的最优位置,其最优位置构成一组次优解集.最后,利用加权质心算法优化次优解集作为未知节点的坐标.实验仿真表明,该方法能有效降低未知节点的定位误差.
      Abstract:
      In order to solve DV-Hop low localization accuracy , a novel localization method was proposed .Firstly, an un-known node chose different hopsize by different beacon nodes .Secondly , according to the idea of Galactic Swarm Optimization , beacon nodes were divided into different populations in the network .Particle swarm optimization algorithm respectively estimated unknown node optimal position , thus constituting a set of sub-optimal solution.Last, unknown node coordinates equaled to weigh-ted average a set of sub-optimal solution .The experiment shows that this method decreases localization error .
      Author: FAN Shi-ping LUO Dan LIU Yan-lin
      作者单位: 重庆邮电大学通信与信息工程学院,重庆,400065
      刊 名: 仪表技术与传感器 ISTICPKU
      年,卷(期): 2017, (1)
      分类号: TP393
      在线出版日期: 2017年3月31日
      基金项目: 国家自然基金专项项目