动态无线传感器网络的改进蒙特卡罗定位算法

An Improved Monte Carlo Localization Algorithm for Mobile Wireless Sensor Networks

针对于无线传感器网络中移动节点的定位问题,在传统蒙特卡罗定位算法的基础上,提出了一种改进算法。该算法通过构建接收信号强度指示测距模型来限制样本区域以求提高采样效率。仿真结果表明,与MCL、MCB等其他蒙特卡罗定位算法相比,改进算法在不同的时间、不同的锚节点密度、不同的节点移动速度等情况下,都具有更好的定位精度。

Aiming at the localization of mobile nodes in wireless sensor networks,an improved algorithm is proposed based on the conventional MCL algorithm.The RSSI ranging model is built in the improved algorithm to restrict the sampling area for improving the sampling efficiency.The simulation result shows that this improved algorithm obtains better localization precision in different time steps,density of anchor nodes and movement velocity compared with other localization algorithms such as MCL and MCB which are based on Monte Carlo method.