基于SVM的WSN移动节点定位算法

针对现有移动传感器网络定位存在错误率较高的问题，提出一种基于向量机技术的网络定位算法。该算法通过向量机技术建立节点测量向量与其位置的关系，节点根据新观察到的信息过滤掉不符合要求的取值范围。使节点持有其之前的运动轨迹样本点集，通过牛顿插值的方法计算其位置方向并更新节点样本点集，样本点通过向量机计算和纠正其坐标位置，从而实现节点的预测定位。仿真实验结果表明，与传统算法相比，该算法在锚节点较少、节点运动速度较快的情况下能保持较低的定位错误率。

Localization Algorithm of Mobile Nodes in WSN Based on SVM

Aiming at the problem of the prevailing higher error rate for the existing mobile sensor network localization, this paper presents a new network localization algorithm based on vector machine technology. This algorithm builds the relationship between the node hop-vector and the location by the vector machine technology and the nodes filter the values which can not accord with demands. The nodes hold the sample point set of their original trajectories, calculate and correct their orientation by Newton interpolation method to upgrade their sample point set, and determines their location coordinates by vector machines to achieve the predicted localization of the nodes. Simulation experimental results show that new algorithm has a lower error rate when compared with other algorithms and still keeps a relatively low error rate especially in the case of less anchor nodes and faster movement speed.