基于反向传播神经网络的WSN节点定位方法研究

The study of WSN node localization method based on back propagation neural network

针对无线传感器网络存在的定位精度问题,基于反向传播神经网络提出一种新的节点定位方法.该方法首先结合时间差测距和信号强度给出了节点定位计算公式,同时结合反向传播神经网络对上述参数进行快速求解.最后结合NS2和MATLAB进行仿真实验,深入研究了影响定位方法的关键因素.通过对比其他定位算法,本方法具有较好的适应性,能够有效降低定位误差.

In order to cut down the localization accuracy problem of wireless sensor network （WSN）, a novel node localization method is proposed with back propagation neural network （BPNN）. At first, the calculation of node localization is presented by ranging interval and signal strength, and the parameters are rapid solving base on BPNN. Finally, a simulation experiment is conducted to study the influence key factor with NS2 and MATLAB. The results show that, compared other localization algorithm, this method has good suitability, and it could effectively reduce the localization error.