Computer Engineering and Applications ›› 2017, Vol. 53 ›› Issue (18): 84-88.DOI: 10.3778/j.issn.1002-8331.1703-0539

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Bounding-Box localization algorithm based on limit partition of estimated rectangle

ZHU Changju, WU Jiaxin, SONG Haisheng, YANG Hongwu   

  1. College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou 730070, China
  • Online:2017-09-15 Published:2017-09-29

极限分割估计矩形的Bounding-Box定位算法

朱长驹,吴佳欣,宋海声,杨鸿武   

  1. 西北师范大学 物理与电子工程学院,兰州 730070

Abstract: Aiming to the problem of low positioning accuracy, in Wireless Sensor Network(WSN), for traditional Bounding-Box algorithm, the method of limit partition is proposed on the basis of Bounding-Box algorithm to improve the localization algorithm. The estimated rectangle produces a desired centroid after partition. While satisfying the conditions of partition, continue partitioning and producing a new desired centroid. If the termination condition is satisfied, the centroid coordinates of the last partition are chosen as the final position of the unknown node. The simulation results suggest that, in case of no additional communication overhead, the improved algorithm reduces the average relative positioning error of the algorithm to a certain extent.

Key words: Wireless Sensor Network(WSN), Bounding-Box algorithm, limit partition, estimated rectangle, desired centroid

摘要: 针对无线传感器网络中Bounding-Box算法定位精度低的问题,在Bounding-Box算法的基础上提出一种极限分割估计矩形的方法来改进定位算法,分割后的估计矩形产生一个待选质心,当满足分割条件时,对估计矩形继续分割,并不断产生待选质心,当满足终止分割条件时,将上一次分割得到的待选质心坐标作为未知节点的最终位置,通过极限分割的方法可以修正未知节点的定位误差。仿真结果表明,在无需增加额外通信开销的情况下,改进的算法在一定程度上降低了算法的平均相对定位误差。

关键词: 无线传感器网络, Bounding-Box算法, 极限分割, 估计矩形, 待选质心