吉林大学学报(理学版) ›› 2019, Vol. 57 ›› Issue (2): 352-356.

• 计算机科学 • 上一篇    下一篇

基于自适应基准值改进的RSSI加权质心定位算法

程超, 蒋志洋, 韩青山, 王宏志   

  1. 长春工业大学  计算机科学与工程学院, 长春 130012
  • 收稿日期:2017-12-24 出版日期:2019-03-26 发布日期:2019-03-26
  • 通讯作者: 王宏志 E-mail:jiangzhiyang921@163.com

Improved RSSI Weighted Centroid Localization AlgorithmBased on Adaptive Reference Value#br#

CHENG Chao, JIANG Zhiyang, HAN Qingshan, WANG Hongzhi   

  1. School of Computer Science and Engineering, Changchun University of Technology, Changchun 130012, China
  • Received:2017-12-24 Online:2019-03-26 Published:2019-03-26
  • Contact: WANG Hongzhi E-mail:jiangzhiyang921@163.com

摘要: 提出一种根据设定接收的信号强度指示基准值改进的加权质心算法. 先通过锚节点向周围发散自身坐标等相关数据包, 然后假设某一参考节点为未知节点, 测得与周围锚节点传播过程中的信号强度损耗值, 判断最小的接收信号强度指示值, 优化样本集合, 将修正的信号指示值参数作为相应新表节点的权重, 并求得定位误差. MATLAB仿真结果表明, 该算法相比于传统算法的定位精度更高, 定位误差波动更小, 且有较强的机动性和可适应性.

关键词: 加权质心定位算法, 接收信号强度, 加权因子, 自适应基准值

Abstract: We proposed an improved weighted centroid algorithm based on setting the received signal strength indication reference value. First, the relevant data packets such as the coordinates were diverted from the anchor node to the surrounding area. Then, assuming that a reference node was an unknown node, the signal intensity loss value in the process of propagation with the surrounding anchor node was measured, the minimum received signal intensity indication value was judged, and the sample set was optimized. The parameters of the revised signal indication value were taken as the weights of the corresponding new table nodes, and the location error was obtained. The simulation results of MATLAB show that, compared with the traditional algorithm, the algorithm has higher location accuracy, smaller fluctuation of location error, and strong mobility and adaptability.

Key words: weighted centroid localization algorithm, received signal intensity, weighting factor, adaptive reference value

中图分类号: 

  • TP391.9