基于跳数分类的改进DV-Hop节点定位算法

发布时间：2018-03-09 09:40

本文选题：无线传感器网络　切入点：节点定位　出处：《传感技术学报》2017年10期 　论文类型：期刊论文

【摘要】：在传统DV-Hop节点定位算法中,不同的网络节点密度使得节点之间不同跳数的平均每跳距离差异较大,跳数越多误差越大。为了减小平均每跳距离差异对节点定位精度的影响,提出一种DV-Hop改进算法。改进算法首先提出跳数分类的策略对网络中不同的跳数进行分类,以减小不同跳数之间平均每跳距离差异的影响,提高节点的定位精度;然后对加权最小二乘估计进行改进,采用改进的权系数取值策略来适应累积误差的非线性变化,从而更好地控制不同跳数在最小二乘估计中的权重,以减小因跳数增加而产生的累积误差,进一步提高节点的定位精度。实验结果表明,改进算法可以有效地减小平均每跳距离差异以及高跳数对节点定位的影响,节点定位性能显著优于传统DV-Hop节点定位算法,相较于对比文献也有一定的提升,并且对不同的网络节点密度具有更好的适应性。
[Abstract]:In the traditional DV-Hop node localization algorithm, different network node density makes the difference of average hop distance between nodes greater, the more hops, the greater the error, in order to reduce the influence of average hop distance difference on node location accuracy. This paper proposes an improved DV-Hop algorithm. Firstly, the improved algorithm proposes the strategy of number of hops classification to classify different hops in the network, so as to reduce the influence of the average distance per hop between different hops and improve the location accuracy of nodes. Then the weighted least square estimation is improved, and the weight of different hops in least square estimation is better controlled by adopting the improved weighting strategy to adapt to the nonlinear variation of cumulative error. The experimental results show that the improved algorithm can effectively reduce the average distance per hop and the influence of the number of high hops on the location of nodes. Node localization performance is significantly better than the traditional DV-Hop node localization algorithm, compared with the comparison of literature also has a certain improvement, and has a better adaptability to different network node density.
【作者单位】：江西理工大学信息工程学院;
【分类号】：TN929.5;TP212.9

【相似文献】