摘要
定位算法作为无线传感器网络的关键技术,在提高节点定位精度和网络效率方面发挥着重要作用。为解决由于定位范围广、信标节点分布随机且稀疏所导致的RSSI测距信息受环境影响定位精度下降的问题,提出了一种基于模糊聚类的协作加权定位算法。使用模糊聚类算法将信标节点分成若干簇,在簇内用三边定位算法对未知节点进行定位,加快定位收敛速度;同时引入RSSI优化机制,通过给RSSI值求得一个加权系数,减小环境因素对本算法产生的影响。仿真结果表明,相比于三边定位算法和协作定位算法,提出的算法定位精确度分别提高了51.25%和20.05%,在定位精度方面更具优势,更适用于信标节点稀疏的应用场景。
As a key technology of wireless sensor networks,positioning algorithm plays an important role in improving node location accuracy and network efficiency.In order to solve the problem that the RSSI ranging information is affected by the environment due to the wide location range,random and sparse distribution of beacon nodes,a cooperative weighted positioning algorithm based on fuzzy clustering is proposed.The beacon node is divided into several clusters by fuzzy clustering algorithm,and the unknown node is located by trilateral positioning algorithm within the cluster to speed up the location convergence.At the same time,the RSSI optimization mechanism is introduced to reduce the impact of environmental factors on the algorithm by obtaining a weighted coefficient for the RSSI value.The simulation results show that compared with the trilateral positioning algorithm and the cooperative positioning algorithm,the positioning accuracy of the proposed algorithm is improved by 51.25%and 20.05%respectively,which is more advantageous in positioning accuracy and more suitable for the application scenarios with sparse beacon nodes.
作者
汪子为
房亮
WANG Zi-wei;FANG Liang(School of Physics and Electronic Information,Yan'an University,Yan'an716000,Shaanxi)
出处
《商洛学院学报》
2022年第6期54-58,共5页
Journal of Shangluo University
关键词
模糊聚类
RSSI权重
三边定位
fuzzy clustering
RSSI Weight
irilateral positioning
