无线传感器网络三维抽样定位

为了减小定位误差、提高算法的适应性，利用三维空间抽样和范围约束的方法，并结合对成功样本点的加权筛选，获得节点的三维估计坐标以实现定位.针对不同的节点功能，算法可以在基于跳数和基于距离两种方式下进行，并采用三种不同的抽样方案对这两种方式进行了分析和比较.初步仿真实验显示了该三维定位算法可以在锚节点比例20%的情况下，定位误差低于通讯半径的25%；测距误差增大到通讯半径的50%时，定位误差不超过通讯半径的35%.

Sampling Based Three-dimensional Localization Algorithm for Wireless Sensor Networks

A three-dimensional localization algorithm is put forward for the sake of reducing location error and improving algorithm applicability. Combined with weighted filtration to successful sample points, it uses the method of sampling in three-dimensional space and range constraint to acquire three-dimensional coordinates of nodes. The algorithm can be executed in hop-based or range-based mode according to different node function. Three sampling schemes are adopted to analyze and compare the localization algorithm. Simulation results show this three-dimensional localization algorithm can respectively achieve location error under 25% and 35% of communication radius when anchor ratio is 20% and ranging error is 50% of communication radius.