基于二维拓扑参数修正评估机制的WSN数据节点定位算法研究

Research on WSN data node localization algorithm based on modified evaluation mechanism of two-dimensional topological parameters

针对传统WSN网络定位过程需要采取锚节点定位的机制存在定位收敛效果差,误差精度难以满足实际需要且需要预设锚节点等不足,提出了一种基于二维拓扑参数修正评估机制的WSN数据节点定位机制。首先,利用WSN节点具有中继聚类特性,采取WSN自身网络中继聚类评估的方式构建二维拓扑参数,根据角度、跳数两个维度,能够实现基于聚类的有效精度评估,在定位过程中采取中继节点聚合评估修正的方式进行一次定位。随后,利用WSN网络具有的角度自适应特性,采取分布列演进方法来完成节点的重定位。仿真实验表明,与超线性一次定位算法（super linear one-time positioning algorithm,SLOP）、混沌三角预估定位算法（chaotic trigonometric prediction positioning algorithm,CTPP）相比,所提算法具有更好的收敛性好与更高的定位精度,能适应信道抖动的复杂环境,具有显著的实际部署价值。

In order to solve the problem with traditional WSN network positioning process, the mechanism of anchor nodelocation is poor in positioning convergence; the accuracy of error is difficult to meet the actual needs and needs the defaultanchor node. It proposes a WSN data node location mechanism based on the two dimensional topology parameter correc- tion evaluation mechanisms. Firstly, the WSN node has the characteristic of relay clustering, and the two dimensional topology parameters are constructed by WSN sell＂ network relay clustering evaluation. Then, using the adaptive feature of WSN network, the distribution column evolution method is adopted to relocate the positioning. The simulation experi- ment shows that this algorithm has better convergence, higher positioning accuracy and can adapt to the complex envi- ronment of channel jitter, and has significant actual deployment value compared with the super linear primary location al- gorithm and the chaotic triangular prediction location algorithm.