基于距离估计的无线传感网络移动节点定位研究

Study on mobile nodes location based on distance estimation for wireless sensor network

针对传统MCL算法定位精度低的不足,提出了一种基于距离估计的改进蒙特卡罗定位算法—DEMCL.首先根据网络连通度、锚节点信息和节点间的相邻关系估计目标节点与锚节点间的距离;然后利用该距离构建新的过滤条件加入算法的过滤阶段,以优化样本集和减小定位误差;最后以Matlab为工具对算法的定位性能进行仿真和分析.仿真结果表明:在同一环境下,与MCL算法和MCB算法相比,DEMCL算法能保证更高的定位精度,同时减少了无效定位的节点数目,网络覆盖率可达到98.83%.

Aiming at the disadvantage of low positioning accuracy of traditional Monte Carlo Localization method (MCL) algorithm, this paper proposes an improved Monte Carlo Localization algorithm?DEMCL, which is based on distance estimation. First, the estimation distance between the unknown nodes and anchor nodes is calculated based on the network connectivity, anchor node information and adjacent relationship of nodes. Then, a new filter condition is added to the filtering phase of the algorithm to optimize the sample set and reduce positioning errors. And the end of the article, Matlab is used to simulate and analyze the performance of the algorithm. The simulation results show that in the same environment, compared with the MCL algorithm and the MCB algorithm, the DEMCL algorithm can ensure higher positioning accuracy, while reducing the number of invalidly located nodes, the network coverage can reach 98.83%.