移动无线传感网中的迭代蒙特卡罗定位算法研究

研究移动无线传感网中的节点定位问题,分析影响蒙特卡罗定位精度的两个因素:观测值和前一时刻的位置样本集,提出一种迭代蒙特卡罗定位算法。该算法中,信标节点的位置信息在每个时间段只被它的邻居节点转发一次,但是接收到该信息的其他节点会保存它们,并在下一时间段将它们与待发送/转发的信息融合成一个数据包进一步转发,增加待定位节点用于估算前几个时间段位置样本集的观测值。待定位节点再利用蒙特卡罗算法迭代计算前面时间段的位置样本集,并充分利用观测值滤除较差样本,从而提高当前时刻的定位精度。仿真实验表明改进算法提高了定位准确度。当信标节点密度较低时,更能体现改进算法的优越性。

Iterative Monte Carlo Localization for Mobile Wireless Sensor Networks

This paper is concerned with the localization problem for mobile Wireless Sensor Networks.Two factors that influence the location accuracy of MCL(Monte Carlo Localization) method are analyzed,and an IMCL(Iterative Monte Carlo Localization) algorithm is proposed.The two factors are observations and the possible location sets from the previous time step.In IMCL,the packet containing location of seed nodes is relayed once in a time interval.However,nodes that receive this packet aggregate it with the message w...