一种基于N-最优阶次序列的无线传感器网络节点定位方法

基于阶次序列的无线传感器网络(Wireless sensor networks, WSN)定位方法是一种新颖的高精度定位方法, 该方法将定位空间划分为不同的子区域, 每个子区域用一条阶次序列唯一标识. 但该方法存在区域边界节点定位误差较大且不能保证平均定位误差最优. 提出了一种基于N-最优阶次序列的节点定位方法. 首先基于无线信号衰减模型产生虚拟测试点, 以参考点为样本, 通过随机采样确定最优N值,然后选择阶次位于前N位的序列所表示的子区域, 对目标进行加权定位. 文中完成了100个节点的仿真实验、15个ZigBee网络硬件节点的室外实验以及10个ZigBee硬件节点的防空洞模拟矿井应用实验. 结果表明, 本文方法有效地降低了平均定位误差, 并改善了边界节点的定位精度.

A New Localization Method for Wireless Sensor Network Nodes Based on N-best Rank Sequence

Rank sequence-based localization method is a novel and high-accuracy wireless sensor networks (WSN) localization technique. The localization space is divided into distinct sub-regions and each is uniquely identified by a rank sequence. However, the localization errors for nodes on the edge of a region are rather large and they are not optimal in view of average localization errors. This paper proposes a new N-best rank sequence localization method. The best value N is first achieved using the random sampling for reference nodes based on a wireless channel fading model, and the coordinates for the target are then computed through selecting the top N rank sequences. We have conducted the simulation with 100 nodes, the outdoor experiment with 15 ZigBee physical nodes, and the air-raid shelter tunnel test with 10 ZigBee nodes. All the results have shown that our method reduces the average localization errors and improves the localization accuracy for nodes on the edge of the region.