摘要
Abstract
The different network node densities made larger difference among average single-hop distance of different hop count values in traditional DV-Hop node localization algorithm,and the error increased with the increase of the hop count value. An improved DV-Hop algorithm was proposed to reduce the influence of the average single-hop distance difference on the node localization accuracy. Firstly,the strategy of hop count classification was proposed to classify the different hop counts in the network,so as to reduce the difference of average single-hop distance between different hop counts,and to enhance the accuracy of node localization. Then,by using the strategy of the improved weight coefficient,the weighted least squares estimation was improved to adapt to the nonlinear variation of the cu-mulative error,which could better control the weight of the different hop counts in the least squares estimation,and further enhance the accuracy of node localization. The experimental results show that the improved algorithm can ef-fectively reduce the influence of the average single-hop distance difference and the large hop count value on the node localization,its node localization performance is obviously superior to traditional DV-Hop node localization al-gorithm,compared with comparative literature also has a certain improvement,and it has better adaptability to differ-ent network node densities.关键词
无线传感器网络/节点定位/DV-Hop算法/跳数分类/加权最小二乘估计Key words
wireless sensor network/node localization/DV-Hop algorithm/hop count classification/weighted least squares estimation分类
信息技术与安全科学
