摘要
节点自定位算法是无线传感器网络的关键技术之一.通过三边比例法,未知节点与任意2个锚节点可计算一对候选共轭位置.用未知节点估计位置作为模糊聚类核心,可以消除共轭干扰并简化聚类迭代过程.用候选位置正态分布概率密度作为模糊隶属度,可降低误差较大锚节点影响,提高定位精度.OPNET仿真证实,模糊聚类算法可用近一次泛洪法通信量,达到22%定位精度.
Positioning algorithm is a key technique of the wireless sensor networks. Few unauthentic anchors introduce great positioning error of range-free positioning algorithm. Trilateral-Proportionality strategy can calculate a pair of candidate conjugate positions from two anchors＇ positions and trilateral proportionality. Generally, the distribution accords with the normal distribution. Using crude measurement location as clustering core and the statistics of distribution as the fuzzy membership grades, the algorithm can exclude conjugate solutions, enhance the precision and simplify the clustering iteration process. Simulation by OPNET showed that precision increased to approach 22% and the traffic decreased to near once controlled flood.
出处
《武汉理工大学学报（交通科学与工程版）》
2009年第6期1203-1206,共4页
Journal of Wuhan University of Technology（Transportation Science & Engineering）
基金
国家自然科学基金项目(批准号:60672122)
高等学校博士学科点科研项目项目(批准号:20070013026)资助
关键词
无线传感器网络
分布式无测距依赖定位
模糊聚类
正态分布
三边比例法
wireless sensor networks
distributed range-free positioning
fuzzy clustering
normal distribution
trilateral-proportionality strategy
